Researcher jobs in Alameda, CA

Join a Leading Applied Research Lab Pushing the Boundaries of Reinforcement Learning Are you passionate about advancing the frontiers of reinforcement learning (RL)? An innovative AI research lab is seeking talented and ambitious scientists to shape the next generation of RL techniques-especially where they intersect with large models and environment generation. About the Role As an AI Research Scientist focused on RL, you will: Develop novel optimization-based methods for automated RL environment generation Establish baselines for evaluating the quality and diversity of RL environments Design infrastructure to create dynamic environments from historical datasets and agent evaluations Drive your own research agenda, contributing directly to the progress of our platform and the broader AI community What We're Looking For PhD (or equivalent experience) in machine learning, computer science or a related field Strong publication record and/or evidence of research impact (open source, deployed systems, etc.) Deep expertise in reinforcement learning and machine learning fundamentals Proficient in Python and at least one modern ML framework (such as PyTorch or JAX) Bonus Points Experience with post-training large language models (LLMs) Demonstrated software engineering skills Ability to communicate research findings effectively to both technical and non-technical audiences

⚡ Research Scientist - Data focus 💊 Foundation Models, AI Research Institute 🌎 San Francisco Bay Area, USA 💸 $200,000 - $350,000 salary + bonus Come join a revolutionary AI research lab in SF Bay Area that is poised to develop & publish high-impact breakthroughs in GenAI - across LLMs and Multimodal AI. As part of the team, you'll work at the intersection of data, large-scale training, and foundation model innovation. You will collaborate with world-class researchers, data scientists, and engineers to solve critical challenges in creating robust, scalable, and reasoning-capable LLMs. Your research will shape the way data is curated, processed, and leveraged to train the next generation of intelligent systems. Responsibilities: Lead research on data-centric approaches for LLMs, including pretraining corpus design, data valuation, and speculative decoding strategies. Develop pipelines to process challenging data sources into structured and reproducible training datasets. Build and optimize agentic data pipelines, integrating retrieval, self-curation, and multi-agent feedback for high-quality training and evaluation data. Collaborate with researchers on alignment and reasoning-focused training that leverage data-driven approaches for improving LLM capabilities. Prototype and deploy evaluation frameworks to measure data quality, coverage, and downstream impact on LLM reasoning. Publish findings at top-tier venues (e.g., NeurIPS, ICLR, ACL, EMNLP) and represent the institute at international conferences. Contribute to open-source tools, datasets, and benchmarks that advance the global foundation model research community. Requirements: Master's degree in Computer Science, Data Science, or a related technical field (PhD strongly preferred) Experience collecting and curating high-quality text data including multi-lingual data. Hands-on experience with large-scale dataset curation and preprocessing for ML/LLM training. Prior works synthesizing complex datasets. Code, math, and agentic data are higher priority Experience with ML infrastructure for scalable training, evaluation, and debugging. Experience at the intersection of data and post-training (RL/SFT) Proven ability to independently drive research questions related to data quality, scaling, or reasoning. Preferred Experience: Experience with retrieval-augmented generation (RAG), agentic data pipelines, or reasoning benchmarks. Contributions to speculative decoding, self-curation, or reinforcement learning from synthetic data. Background in knowledge graphs, semantic search, or indexing systems. Strong publication record in leading AI conferences. Prior contributions to open-source ML data tools or benchmarks. Prior work on speculative decoding/contributions to LLM serving engines Prior work on training LLM-as-a-judge Deep expertise with tokenization/training tokenizers Why apply: Opportunity to build out a new division at the forefront of AI innovation FAANG competitive salary & package Work alongside superstars from FAANG labs & leading AI companies Medical, Dental and Vision Insurance Relocation package available 🌎 San Francisco Bay Area, USA 📧 Interested in applying? Please click on the ‘Easy Apply' button or alternatively email me your resume at ************************

Title: AI Research Scientist Responsibilities: Design, execute, and analyze machine learning experiments, establishing strong baselines and selecting appropriate evaluation metrics. Stay up to date with the latest AI research; identify, adapt, and validate novel techniques for company-specific use cases. Define rigorous evaluation protocols, including offline metrics, user studies, and adversarial (red team) testing to ensure statistical soundness. Specify data and annotation requirements; develop annotation guidelines and oversee quality control processes. Collaborate closely with domain experts, product managers, and engineering teams to refine problem statements and operational constraints. Develop reusable research assets such as datasets, modular code components, evaluation suites, and comprehensive documentation. Work alongside ML Engineers to optimize training and inference pipelines, ensuring seamless integration into production systems. Contribute to academic publications and represent the company in research communities, as needed. Educational Qualifications: Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field is strongly preferred. Candidates with a master's degree and exceptional research or industry experience will also be considered. Industry Experience: 3-5 years of experience in AI/ML research roles, ideally in applied or product-focused environments. Demonstrated success in delivering research-driven solutions that have been deployed in production. Experience collaborating in cross-functional teams across research, engineering, and product. Publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ACL, CVPR) are a plus. Technical Skills: Strong foundational knowledge in machine learning and deep learning algorithms. Hands-on experience with PEFT/LoRA, adapters, fine-tuning techniques, and RLHF/RLAIF (e.g., PPO, DPO, GRPO). Ability to read, implement, and adapt state-of-the-art research papers to real-world use cases. Proficiency in hypothesis-driven experimentation, ablation studies, and statistically sound evaluations. Advanced programming skills in Python (preferred), C++, or Java. Experience with deep learning frameworks such as PyTorch, Hugging Face, NumPy, etc. Strong mathematical foundations in probability, linear algebra, and calculus. Domain expertise in one or more areas: natural language processing (NLP), symbolic reasoning, speech processing, etc. Ability to translate research insights into roadmaps, technical specifications, and product improvements. AI Research Scientist | Machine Learning | Deep Learning | Natural Language Processing | LLM | Hybrid | San Jose, CA

Early-stage (vertical RL) company looking to hire a Sr. Applied RS with a strong background in reinforcement learning. Qualifications: Applied Research with MS or PhD in a related field and 4 + years industry experience in deep learning and 2+ years with reinforcement learning Successful track record as a self-starter in 0->1 scenarios with a proven ability to take SOTA models into production Please note: Due to the selective nature of this service and the volume of applicants we typically receive from our job postings, a follow-up email will not be sent until a match is identified with one of the startup investments in our portfolio. About Us: Greylock is an early-stage investor in hundreds of remarkable companies including Airbnb, LinkedIn, Dropbox, Workday, Cloudera, Facebook, Instagram, Roblox, Coinbase, Palo Alto Networks, among others. More can be found about us here: ********************* We are full-time, salaried employees of Greylock who provide free candidate referrals/introductions to our active investments to help them grow/succeed (as one of the many services we provide). Please note: We are not recruiting for any roles within Greylock at this time. This job posting is for direct employment with a startup in our portfolio.

, December 8th-May 31st, 2026 Hours: Monday through Friday 8:00-5:00 PM Onsite, in Menlo Park, CA Required Skills & Experience -Bachelor's degree or relevant coursework in engineering, research, or a related field (or equivalent experience). -Strong attention to detail and organizational skills. -Basic technical aptitude and familiarity with handling electronic devices. -Experience with FedEx shipping systems or package tracking preferred. - Basic knowledge of microsoft excel - Excellent communication and teamwork abilities. Job Description Overview: Insight Global is seeking a detail-oriented Research Assistant to support the deployment of prototype equipment for upcoming remote user studies. This role is part of a dynamic team responsible for testing and preparing electronic prototype devices before they are shipped to study participants. Key Responsibilities: - Assist in testing and validating prototype electronic devices to ensure full functionality prior to shipment. -Prepare, package, and ship devices to participants involved in remote, in-home studies using FedEx as the primary shipping method. -Track shipments and ensure timely delivery and return of study equipment. -Maintain detailed records of device testing, configurations, and shipping status. -Collaborate closely with research and engineering teams to ensure accuracy, quality, and timely deployment. -Troubleshoot and document any technical issues during pre-deployment testing. -Document in excel for additional tracking purposes Why Join Us: This is an exciting opportunity to contribute to cutting-edge research by ensuring the successful deployment of innovative technology.

Amber Bio is a biotechnology company pioneering new gene editing modalities using multi-kilobase edits to reach previously undruggable patient populations. Founded by pioneers in the CRISPR field from leading institutions for gene editing research, the company is developing a first-of-its-kind RNA editing platform that can correct thousands of bases at once, thereby correcting genetic mutations safely and reversibly. If you are interested in building a new frontier in genetic medicine, we welcome you to apply. Job Description: High-Throughput Screening Research Associate II, III (Biodesigner II, III) Responsibilities: Perform massively parallel reporter assays and high-throughput screens across diverse cellular contexts using cellular and molecular readouts. Develop and execute molecular biology workflows such as vector design and cloning, DNA/RNA extraction, RT-PCR, qPCR, and next-generation sequencing. Support cell culture activities and experiments in multiple cell lines, at small and large scales. Design and execute cell-based assays (AAV/lentiviral transduction, transfection, flow cytometry, immunostaining, and other plate reader assays). Engineer and characterize cell-based systems using synthetic biology tools and techniques. Conduct and troubleshoot experiments, independently and in collaboration with colleagues, to optimize screening throughput, sensitivity, and specificity. Proactively troubleshoot technical issues and recommend potential corrective actions based on personal observations and literature searches. Prepare summaries of data and present internally to colleagues and management. Draft SOPs, follow protocols, diligently document experimental data in lab notebooks, and organize and maintain electronic work records. Author scientific reports and data summaries. Collaborate with cross-functional teams to meet project goals, bridging early discovery with high-throughput screens to nominate and optimize candidates for further characterization. Qualifications: Bachelor's or Master's degree in Biology, Biochemistry, Chemical Engineering, Biological Engineering, or a related field. At least 2 years of industry wet lab experience. Mammalian cell culture experience (culturing, transfecting and transducing cells, and DNA/RNA purification from cells). Molecular biology expertise (vector design and cloning, qPCR, primer and probe design, DNA/RNA extraction workflows) Critical thinker with excellent communication skills who thrives in a multidisciplinary, fast-paced team environment. Strong written and verbal communication skills. Preference will be given to those who display: High throughput screening assay development in an industry setting. High motivation, with a strong work ethic and dedication to generating impact. Attention to detail, with the ability to extract deep insights from data. First-principles thinking, and an ability to refine one's intuition based on additional data. Ability to go from ideation to data in an independent fashion. Long-term personal vision with defined career goals. High EQ with team-oriented thinking. Experience with pooled, high-throughput screens using next-generation sequencing-based readouts, and/or preparing screening plasmid libraries from synthesized oligo arrays. Experience with CRISPR-Cas systems and/or gene editing and delivery technologies. Experience preparing next-generation sequencing libraries (Illumina, PacBio, and/or Nanopore platforms). If you have a passion for advancing gene editing technologies and desire to be part of a pioneering biotech company, we encourage you to apply and join our ambitious team. Please apply directly through LinkedIn. Amber Bio is an equal-opportunity employer and encourages applications from candidates of diverse backgrounds. We value diversity and are committed to creating an inclusive and supportive work environment for all employees.

Please note this posting is to advertise potential job opportunities. This exact role may not be open today but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens. Applications are accepted until further notice. **Meet the Team** Join a collaborative team of researchers and engineers dedicated to unlocking insights from substantial volumes of structured, unstructured, transactional, and real-time data. Together, we analyze diverse data sources to understand customer usage patterns and deliver actionable, impactful insights using advanced metrics, algorithms, and statistical techniques. **Your Impact** As an AI Research Intern, you will contribute to sophisticated research in large language models (LLMs), natural language processing (NLP), and multimodal deep learning. Working with senior researchers and cross-functional teams, you'll help build, implement, and evaluate machine learning models and algorithms. You'll participate in data collection, preprocessing, and analysis, and assist in developing and fine-tuning AI models for a variety of applications. Your expertise in data manipulation, model building, and database design will help transform raw data into important insights, while you continue to develop your skills with the latest tools and frameworks. You will also support research initiatives by creating experiments, comparing algorithms, tuning hyperparameters, and documenting results. In addition, you'll share findings with the team, contribute to reports and presentations, and help onboard new team members. Through collaboration and ongoing learning, your work will help identify business and research opportunities, drive strategic decisions, and advance the field of AI at Cisco. **Minimum Qualifications** + Currentlyenrolled in an undergraduate degree program. Relevant fieldsinclude:Relevant fieldsinclude:Computer Science, Electrical Engineering, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Software Engineering, ora relatedprogram. + Proficiencyin software development, with experience in relevant programming languages (such as Python and Go) and associated tools. + Ability to analyze and interpret data using statistical methods or data analysis tools (e.g., Excel, pandas, NumPy). **Preferred Qualifications** + Experience working with inference engines (e.g.,vLLM, Triton,TorchServe) for LLM serving and optimization. + Familiarity with containerization and cloud platforms (such as Docker and AWS), as well as distributed systems for scaling and deploying AI models. + Familiarity with agentic AI concepts, agent frameworks, and related applications. + Experience training large language models (LLMs)-including modeling, optimization, fine-tuning, and serving-using Python and common AI libraries (such as TensorFlow,PyTorch, or Hugging Face Transformers), asevidencedby academic, project, or professional work. + Understanding ofmachine learning, deep learning, and natural language processing concepts, as proven through academic, project, or professional work. ProductIntern26 **Why Cisco?** At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. We are Cisco, and our power starts with you. **Message to applicants applying to work in the U.S. and/or Canada:** Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process. U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time. U.S. employees are eligible for paid time away as described below, subject to Cisco's policies: + 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees + 1 paid day off for employee's birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco + Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees + Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations) + 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next + Additional paid time away may be requested to deal with critical or emergency issues for family members + Optional 10 paid days per full calendar year to volunteer For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco's policies. Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows: + .75% of incentive target for each 1% of revenue attainment up to 50% of quota; + 1.5% of incentive target for each 1% of attainment between 50% and 75%; + 1% of incentive target for each 1% of attainment between 75% and 100%; and + Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation. For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid. The applicable full salary ranges for this position, by specific state, are listed below: New York City Metro Area: $44,000.00 - $185,000.00 Non-Metro New York state & Washington state: $44,000.00 - $185,000.00 * For quota-based sales roles on Cisco's sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined. ** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements. Cisco is an Affirmative Action and Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis. Cisco will consider for employment, on a case by case basis, qualified applicants with arrest and conviction records.

Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone-from emerging artists to global brands-everything they need to design and deliver exceptional digital experiences! We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! The Opportunity Reporting directly to the Director of the Digital Experience Marketing and Integrated GTM Strategy, this role will drive high-impact marketing initiatives that leverage agentic capabilities to align Adobe's enterprise go-to-market (GTM) strategy with customer needs, sales plays, and product innovation. The ideal candidate will bring a strong mix of strategic thinking, cross-functional leadership, and operational rigor to drive measurable business outcomes across the funnel. What You'll Do You'll work cross-functionally to drive strategic initiatives that span AI-assisted Marketing Capabilities, Integrated GTM Strategy & Alignment, and Translating Account, Persona & Content Strategy into Actionable Insights, Vision-setting and Storytelling. This is a high-visibility role with exposure to senior leadership and opportunities to shape how Adobe delivers experiences to enterprise customers. Key contributions: * Develop AI-Driven Marketing Capabilities: Collaborate on initiatives to develop agentic capabilities for Business Development Reps and Marketers; scoping use cases and translating data into actionable insights and next-best-action recommendations. Support Proof-of-Concept testing to improve agentic capabilities and recommendations. * Foster Integrated GTM Strategy & Alignment: Support the development of strategies to deliver unified customers experiences by synthesizing data from multiple sources (CRM, web, campaign, sales). Partner with Product Marketing, Sales Strategy, and Analytics to shape our unified approach to customers and ensure alignment with sales plays, product priorities, and customer personas. * Translate Account, Persona, & Content Strategy and Actionable Insights: Contribute to the creation and evolution of marketing scorecards and dashboards (e.g., Power BI, CJA B2B), helping teams translate data into actionable insights to inform GTM prioritization. Assist in building and maintaining dashboards, heatmaps, and prioritization tools to support targeted engagement strategies. * Cross-Functional Leadership: Lead cross-functional workstreams with stakeholders across Enterprise Marketing, PMM, Sales, Content Strategy, ACS, and DX Products to drive alignment and execution. Experience We're seeking a highly analytical and strategic thinker to join our Integrated GTM Strategy & PMO team. This role is ideal for someone with a strong foundation in marketing, data analytics, decision sciences, or strategy consulting, and a passion for driving business impact through customer-centric, data-informed marketing strategies. * Currently enrolled in a full-time MBA program graduating between December 2025 - June 2026 * Exceptional analytical and quantitative problem solving skills, including conducting research, analyzing data, developing hypotheses, and synthesizing recommendations * Exceptional written and verbal communication skills with the ability to influence both peers and leaders * Experience in B2B marketing, GTM strategy, or marketing operations preferred * Proven ability to lead cross-functional initiatives and influence senior stakeholders. * Familiarity with AI-powered marketing tools, CRM systems (e.g., Salesforce), and campaign orchestration platforms preferred * Excellent communication and storytelling skills, with a track record of translating complex data into compelling narratives. Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $84,300 -- $163,400 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP). In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award. State-Specific Notices: California: Fair Chance Ordinances Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances. Colorado: Application Window Notice Dec 31 2025 12:00 AM If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs. Massachusetts: Massachusetts Legal Notice It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call **************.

How you will make 10x impact: General description: A machine learning/artificial intelligence specialist with experience in LLM and reinforcement learning post training. * Collaborating with the X Project team to design and develop machine learning approaches/algorithms to support the project's mission * Understanding the project's goals and challenges and conduct relevant literature surveys * Suggesting agentic RL solutions in which machines/approaches/algorithms/models can apply to those challenges * Prototype/train/evaluate RL algorithms, tools and components of large scale AI systems * Engaging with the resident community during the program, engaging with the X community, attending colloquia and tech talks. This project aims to push the limits of science and modeling as we know them and to prove how ML can radically accelerate our understanding of the world * Location: X's headquarters in Mountain View, CA * Start Date(s): ~January 2026 * Duration: a flexible full-time 4 mo. to 1 year program based on project team needs and your availability Throughout your AI Residency you can expect: * To be embedded into one of our confidential or public X projects * To get paid competitively and receive benefits * To be a part of a lively community of AI and ML Residents * To attend tech-talks with AI leaders from across X What you should have: * Currently enrolled in a PhD program in a STEM field such as CS, Physics, Engineering or Mathematics/Statistics with a strong interest in machine learning. * Strong experience with one or more general purpose programming languages such as Python, C/C++. * Experience with reinforcement learning (RL) and large language models (LLMs). * Ability to set up RL infrastructure and synthetic data generation pipelines. * Familiarity with operations research (OR) problems and their formalization. * Knowledge of basic ontologies and programmatically constructing knowledge graphs (KG) from structured and unstructured data. It'd be great if you also had these: * Open-source projects that demonstrate relevant skills and/or publications in relevant conferences and journals (e.g. NeurIPS, ICML, ICLR, CVPR, ICCV, COLM, ACL/EMNLP, ICASSP). * Experience with GRPO/DAPO based online reinforcement learning with LLMs(7B+) on multi-GPU settings. * Ability to produce code (e.g., in Google OR-Tools) and define rewards for formalized optimization problems. * Experience translating natural language into formal graph query languages (Cypher, SPARQL). * Experience using frontier LLMs (e.g., Gemini-Pro) to generate large-scale, high-quality synthetic datasets with automated verification steps. Additional public information: ****************************************************************************************** ******************************************************************************************************** The US base salary range for this position is $109,000 - $150,000 + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include benefits.

SUPERCOMPUTING AI LAB W/ MULTIMODAL GENERAL AGENT AI STARTUP - SERIES A $1.2B VALUATION Goliath Partners has exclusively teamed up with an early stage startup AI Lab in SF currently valued at over $1B just after announcing their Series A. The firm has fundamental research bets on next-gen model architectures for long term memory and continual learning. Have lots of GPUs and are planning to get to frontier soon on the model side. Funding wise, their Series A was led by none other than Jann Tallinn. Jann has only led two other Series A's in the past - DeepMind and Anthropic! The team includes ex-DeepMind, Nvidia, Anthropic and Twitter professionals, and they are operating at the cutting edge of the AI space. They're hiring an ML Research Engineer to: Design and implement autonomous agents that can code, reason, and self-verify across real software environments Build full-stack infrastructure for prompt routing, task planning, retrieval, and sandboxed execution Apply post-training techniques (SFT, DPO, RLHF) and build eval benchmarks for multi-step reasoning and coding tasks Total Comp: $300-325k from a base perspective. Equity will also be involved at anywhere from .1% - 1% (equaling $1-10M in equity). If this sounds interesting, I'd love to share more. Please apply with an updated copy of your resume and Goliath will get in touch!

Join the Frontier of AI-Driven Hardware Design Are you passionate about pushing the boundaries of artificial intelligence and eager to see your research power the next generation of computational hardware? We're a stealth-mode AI research and product lab on a mission to revolutionize chip design. Our team is reimagining how custom silicon is created-using advanced AI to dramatically accelerate and optimize the process, making ultra-efficient, domain-specific chips a reality. About Us Founded by leading minds from top universities and industry labs, our team brings together AI researchers and engineers from organizations like DeepMind, Meta, Apple, and Intel. We're backed by world-class investors, including renowned scientists, professors, and founders in the hardware and AI space. Here, you'll work alongside pioneers at the intersection of machine learning and hardware, building the intelligence layer for tomorrow's computing revolution. Your Role: Founding AI Researcher (ML) As a founding member of our technical team, you'll be at the heart of developing and deploying AI models that transform chip design. You'll tackle challenges like code generation, verification, architectural exploration, and multimodal reasoning-building multi-agent systems that can design, optimize, and verify real silicon. This is a hands-on, 0→1 opportunity: you'll own the full ML lifecycle, from data pipelines and model training to deployment and iteration, collaborating closely with hardware and product experts.You'll experiment at the bleeding edge of LLMs, reinforcement learning, and graph-based methods for EDA, defining how AI will shape the future of hardware What We're Looking For Academic Background: PhD in Computer Science, EECS, Mathematics, or a related field (or BS/MS with strong research engineering experience at leading labs or startups). AI/ML Expertise: Deep experience building end-to-end ML pipelines, including data curation, model training, and post-training using RL. Proven ability to take models from research to real-world deployment. Technical Skills: Hands-on with LLM/VLM deployment (vLLM, sg Lang, LM Studio, Ollama, etc.) and distributed training (QLoRA, ZeRO, CUDA, PyTorch Parallelism). Experience with RL post-training workflows, reward modeling, and environment design. Track record in code generation, reasoning, and tool use-especially in structured domains. Builder Mindset: Fast-moving, able to prototype, benchmark, and productionize ML pipelines with tight feedback loops. Passion: Excited to push the state-of-the-art in AI for real-world engineering challenges. Bonus Points: Experience at leading AI labs (OpenAI, DeepMind, Anthropic, etc.). Publications in top ML or EDA conferences. Background in hardware design or verification (not required). Why Join Us? Impact: Shape the future of AI-driven chip design from the ground up. Ownership: Significant autonomy and a meaningful equity stake. Growth: Work with a world-class team on cutting-edge challenges. Culture: Fast-paced, collaborative, and mission-driven environment. Ready to help define how AI will design the hardware of tomorrow? Apply now and join us at the frontier of AI and hardware innovation!

⚡ Research Scientist - Data focus 💊 Foundation Models, AI Research Institute 🌎 San Francisco Bay Area, USA 💸 $200,000 - $350,000 salary + bonus Come join a revolutionary AI research lab in SF Bay Area that is poised to develop & publish high-impact breakthroughs in GenAI - across LLMs and Multimodal AI. As part of the team, you'll work at the intersection of data, large-scale training, and foundation model innovation. You will collaborate with world-class researchers, data scientists, and engineers to solve critical challenges in creating robust, scalable, and reasoning-capable LLMs. Your research will shape the way data is curated, processed, and leveraged to train the next generation of intelligent systems. Responsibilities: Lead research on data-centric approaches for LLMs, including pretraining corpus design, data valuation, and speculative decoding strategies. Develop pipelines to process challenging data sources into structured and reproducible training datasets. Build and optimize agentic data pipelines, integrating retrieval, self-curation, and multi-agent feedback for high-quality training and evaluation data. Collaborate with researchers on alignment and reasoning-focused training that leverage data-driven approaches for improving LLM capabilities. Prototype and deploy evaluation frameworks to measure data quality, coverage, and downstream impact on LLM reasoning. Publish findings at top-tier venues (e.g., NeurIPS, ICLR, ACL, EMNLP) and represent the institute at international conferences. Contribute to open-source tools, datasets, and benchmarks that advance the global foundation model research community. Requirements: Master's degree in Computer Science, Data Science, or a related technical field (PhD strongly preferred) Experience collecting and curating high-quality text data including multi-lingual data. Hands-on experience with large-scale dataset curation and preprocessing for ML/LLM training. Prior works synthesizing complex datasets. Code, math, and agentic data are higher priority Experience with ML infrastructure for scalable training, evaluation, and debugging. Experience at the intersection of data and post-training (RL/SFT) Proven ability to independently drive research questions related to data quality, scaling, or reasoning. Preferred Experience: Experience with retrieval-augmented generation (RAG), agentic data pipelines, or reasoning benchmarks. Contributions to speculative decoding, self-curation, or reinforcement learning from synthetic data. Background in knowledge graphs, semantic search, or indexing systems. Strong publication record in leading AI conferences. Prior contributions to open-source ML data tools or benchmarks. Prior work on speculative decoding/contributions to LLM serving engines Prior work on training LLM-as-a-judge Deep expertise with tokenization/training tokenizers Why apply: Opportunity to build out a new division at the forefront of AI innovation FAANG competitive salary & package Work alongside superstars from FAANG labs & leading AI companies Medical, Dental and Vision Insurance Relocation package available 🌎 San Francisco Bay Area, USA 📧 Interested in applying? Please click on the ‘Easy Apply' button or alternatively email me your resume at ************************

Series A company looking to hire a Sr. Applied RS with a good background in multi-agent reinforcement learning. The related challenge is figuring out how to use feedback from an objective function on (consumer) pricing to reinforce a multi-agent enterprise system (many components). Qualifications: Applied Research with MS or PhD in a technical field and 4 + years relevant industry experience Successful track record as a self-starter in 0->1 scenarios with a proven ability to take SOTA models into production Please note: Due to the selective nature of this service and the volume of applicants we typically receive from our job postings, a follow-up email will not be sent until a match is identified with one of the startup investments in our portfolio. About Us: Greylock is an early-stage investor in hundreds of remarkable companies including Airbnb, LinkedIn, Dropbox, Workday, Cloudera, Facebook, Instagram, Roblox, Coinbase, Palo Alto Networks, among others. More can be found about us here: ********************* We are full-time, salaried employees of Greylock who provide free candidate referrals/introductions to our active investments to help them grow/succeed (as one of the many services we provide).

Amber Bio is a biotechnology company pioneering new gene editing modalities using multi-kilobase edits to reach previously undruggable patient populations. Founded by pioneers in the CRISPR field from leading institutions for gene editing research, the company is developing a first-of-its-kind RNA editing platform that can correct thousands of bases at once, thereby correcting genetic mutations safely and reversibly. If you are interested in building a new frontier in genetic medicine, we welcome you to apply. Job Description: High-Throughput Screening Research Associate II, III (Biodesigner II, III) Responsibilities: Perform massively parallel reporter assays and high-throughput screens across diverse cellular contexts using cellular and molecular readouts. Develop and execute molecular biology workflows such as vector design and cloning, DNA/RNA extraction, RT-PCR, qPCR, and next-generation sequencing. Support cell culture activities and experiments in multiple cell lines, at small and large scales. Design and execute cell-based assays (AAV/lentiviral transduction, transfection, flow cytometry, immunostaining, and other plate reader assays). Engineer and characterize cell-based systems using synthetic biology tools and techniques. Conduct and troubleshoot experiments, independently and in collaboration with colleagues, to optimize screening throughput, sensitivity, and specificity. Proactively troubleshoot technical issues and recommend potential corrective actions based on personal observations and literature searches. Prepare summaries of data and present internally to colleagues and management. Draft SOPs, follow protocols, diligently document experimental data in lab notebooks, and organize and maintain electronic work records. Author scientific reports and data summaries. Collaborate with cross-functional teams to meet project goals, bridging early discovery with high-throughput screens to nominate and optimize candidates for further characterization. Qualifications: Bachelor's or Master's degree in Biology, Biochemistry, Chemical Engineering, Biological Engineering, or a related field. At least 2 years of industry wet lab experience. Mammalian cell culture experience (culturing, transfecting and transducing cells, and DNA/RNA purification from cells). Molecular biology expertise (vector design and cloning, qPCR, primer and probe design, DNA/RNA extraction workflows) Critical thinker with excellent communication skills who thrives in a multidisciplinary, fast-paced team environment. Strong written and verbal communication skills. Preference will be given to those who display: High throughput screening assay development in an industry setting. High motivation, with a strong work ethic and dedication to generating impact. Attention to detail, with the ability to extract deep insights from data. First-principles thinking, and an ability to refine one's intuition based on additional data. Ability to go from ideation to data in an independent fashion. Long-term personal vision with defined career goals. High EQ with team-oriented thinking. Experience with pooled, high-throughput screens using next-generation sequencing-based readouts, and/or preparing screening plasmid libraries from synthesized oligo arrays. Experience with CRISPR-Cas systems and/or gene editing and delivery technologies. Experience preparing next-generation sequencing libraries (Illumina, PacBio, and/or Nanopore platforms). If you have a passion for advancing gene editing technologies and desire to be part of a pioneering biotech company, we encourage you to apply and join our ambitious team. Please apply directly through LinkedIn. Amber Bio is an equal-opportunity employer and encourages applications from candidates of diverse backgrounds. We value diversity and are committed to creating an inclusive and supportive work environment for all employees.

Please note this posting is to advertise potential job opportunities. This exact role may not be open today but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens. Applications are accepted until further notice. **Meet the Team** Join a collaborative team of researchers and engineers dedicated to unlocking insights from substantial volumes of structured, unstructured, transactional, and real-time data. Together, we analyze diverse data sources to understand customer usage patterns and deliver actionable, impactful insights using advanced metrics, algorithms, and statistical techniques. **Your Impact** As an AI Research Intern, you will contribute to sophisticated research in large language models (LLMs), natural language processing (NLP), and multimodal deep learning. Working with senior researchers and cross-functional teams, you'll help build, implement, and evaluate machine learning models and algorithms. You'll participate in data collection, preprocessing, and analysis, and assist in developing and fine-tuning AI models for a variety of applications. Your expertise in data manipulation, model building, and database design will help transform raw data into important insights, while you continue to develop your skills with the latest tools and frameworks. You will also support research initiatives by creating experiments, comparing algorithms, tuning hyperparameters, and documenting results. In addition, you'll share findings with the team, contribute to reports and presentations, and help onboard new team members. Through collaboration and ongoing learning, your work will help identify business and research opportunities, drive strategic decisions, and advance the field of AI at Cisco. **Minimum Qualifications** + Currentlyenrolled in an undergraduate degree program. Relevant fieldsinclude:Relevant fieldsinclude:Computer Science, Electrical Engineering, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Software Engineering, ora relatedprogram. + Proficiencyin software development, with experience in relevant programming languages (such as Python and Go) and associated tools. + Ability to analyze and interpret data using statistical methods or data analysis tools (e.g., Excel, pandas, NumPy). **Preferred Qualifications** + Experience working with inference engines (e.g.,vLLM, Triton,TorchServe) for LLM serving and optimization. + Familiarity with containerization and cloud platforms (such as Docker and AWS), as well as distributed systems for scaling and deploying AI models. + Familiarity with agentic AI concepts, agent frameworks, and related applications. + Experience training large language models (LLMs)-including modeling, optimization, fine-tuning, and serving-using Python and common AI libraries (such as TensorFlow,PyTorch, or Hugging Face Transformers), asevidencedby academic, project, or professional work. + Understanding ofmachine learning, deep learning, and natural language processing concepts, as proven through academic, project, or professional work. ProductIntern26 **Why Cisco?** At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. We are Cisco, and our power starts with you. **Message to applicants applying to work in the U.S. and/or Canada:** Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process. U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time. U.S. employees are eligible for paid time away as described below, subject to Cisco's policies: + 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees + 1 paid day off for employee's birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco + Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees + Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations) + 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next + Additional paid time away may be requested to deal with critical or emergency issues for family members + Optional 10 paid days per full calendar year to volunteer For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco's policies. Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows: + .75% of incentive target for each 1% of revenue attainment up to 50% of quota; + 1.5% of incentive target for each 1% of attainment between 50% and 75%; + 1% of incentive target for each 1% of attainment between 75% and 100%; and + Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation. For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid. The applicable full salary ranges for this position, by specific state, are listed below: New York City Metro Area: $44,000.00 - $185,000.00 Non-Metro New York state & Washington state: $44,000.00 - $185,000.00 * For quota-based sales roles on Cisco's sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined. ** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements. Cisco is an Affirmative Action and Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis. Cisco will consider for employment, on a case by case basis, qualified applicants with arrest and conviction records.

SUPERCOMPUTING AI LAB W/ MULTIMODAL GENERAL AGENT AI STARTUP - SERIES A $1.2B VALUATION Goliath Partners has exclusively teamed up with an early stage startup AI Lab in SF currently valued at over $1B just after announcing their Series A. The firm has fundamental research bets on next-gen model architectures for long term memory and continual learning. Have lots of GPUs and are planning to get to frontier soon on the model side. Funding wise, their Series A was led by none other than Jann Tallinn. Jann has only led two other Series A's in the past - DeepMind and Anthropic! The team includes ex-DeepMind, Nvidia, Anthropic and Twitter professionals, and they are operating at the cutting edge of the AI space. They're hiring an ML Research Engineer to: Design and implement autonomous agents that can code, reason, and self-verify across real software environments Build full-stack infrastructure for prompt routing, task planning, retrieval, and sandboxed execution Apply post-training techniques (SFT, DPO, RLHF) and build eval benchmarks for multi-step reasoning and coding tasks Total Comp: $300-325k from a base perspective. Equity will also be involved at anywhere from .1% - 1% (equaling $1-10M in equity). If this sounds interesting, I'd love to share more. Please apply with an updated copy of your resume and Goliath will get in touch!

Join a Leading Applied Research Lab Pushing the Boundaries of Reinforcement Learning Are you passionate about advancing the frontiers of reinforcement learning (RL)? An innovative AI research lab is seeking talented and ambitious scientists to shape the next generation of RL techniques-especially where they intersect with large models and environment generation. About the Role As an AI Research Scientist focused on RL, you will: Develop novel optimization-based methods for automated RL environment generation Establish baselines for evaluating the quality and diversity of RL environments Design infrastructure to create dynamic environments from historical datasets and agent evaluations Drive your own research agenda, contributing directly to the progress of our platform and the broader AI community What We're Looking For PhD (or equivalent experience) in machine learning, computer science or a related field Strong publication record and/or evidence of research impact (open source, deployed systems, etc.) Deep expertise in reinforcement learning and machine learning fundamentals Proficient in Python and at least one modern ML framework (such as PyTorch or JAX) Bonus Points Experience with post-training large language models (LLMs) Demonstrated software engineering skills Ability to communicate research findings effectively to both technical and non-technical audiences

⚡ Research Scientist - Data focus 💊 Foundation Models, AI Research Institute 🌎 San Francisco Bay Area, USA 💸 $200,000 - $350,000 salary + bonus Come join a revolutionary AI research lab in SF Bay Area that is poised to develop & publish high-impact breakthroughs in GenAI - across LLMs and Multimodal AI. As part of the team, you'll work at the intersection of data, large-scale training, and foundation model innovation. You will collaborate with world-class researchers, data scientists, and engineers to solve critical challenges in creating robust, scalable, and reasoning-capable LLMs. Your research will shape the way data is curated, processed, and leveraged to train the next generation of intelligent systems. Responsibilities: Lead research on data-centric approaches for LLMs, including pretraining corpus design, data valuation, and speculative decoding strategies. Develop pipelines to process challenging data sources into structured and reproducible training datasets. Build and optimize agentic data pipelines, integrating retrieval, self-curation, and multi-agent feedback for high-quality training and evaluation data. Collaborate with researchers on alignment and reasoning-focused training that leverage data-driven approaches for improving LLM capabilities. Prototype and deploy evaluation frameworks to measure data quality, coverage, and downstream impact on LLM reasoning. Publish findings at top-tier venues (e.g., NeurIPS, ICLR, ACL, EMNLP) and represent the institute at international conferences. Contribute to open-source tools, datasets, and benchmarks that advance the global foundation model research community. Requirements: Master's degree in Computer Science, Data Science, or a related technical field (PhD strongly preferred) Experience collecting and curating high-quality text data including multi-lingual data. Hands-on experience with large-scale dataset curation and preprocessing for ML/LLM training. Prior works synthesizing complex datasets. Code, math, and agentic data are higher priority Experience with ML infrastructure for scalable training, evaluation, and debugging. Experience at the intersection of data and post-training (RL/SFT) Proven ability to independently drive research questions related to data quality, scaling, or reasoning. Preferred Experience: Experience with retrieval-augmented generation (RAG), agentic data pipelines, or reasoning benchmarks. Contributions to speculative decoding, self-curation, or reinforcement learning from synthetic data. Background in knowledge graphs, semantic search, or indexing systems. Strong publication record in leading AI conferences. Prior contributions to open-source ML data tools or benchmarks. Prior work on speculative decoding/contributions to LLM serving engines Prior work on training LLM-as-a-judge Deep expertise with tokenization/training tokenizers Why apply: Opportunity to build out a new division at the forefront of AI innovation FAANG competitive salary & package Work alongside superstars from FAANG labs & leading AI companies Medical, Dental and Vision Insurance Relocation package available 🌎 San Francisco Bay Area, USA 📧 Interested in applying? Please click on the ‘Easy Apply' button or alternatively email me your resume at ************************

Amber Bio is a biotechnology company pioneering new gene editing modalities using multi-kilobase edits to reach previously undruggable patient populations. Founded by pioneers in the CRISPR field from leading institutions for gene editing research, the company is developing a first-of-its-kind RNA editing platform that can correct thousands of bases at once, thereby correcting genetic mutations safely and reversibly. If you are interested in building a new frontier in genetic medicine, we welcome you to apply. Job Description: High-Throughput Screening Research Associate II, III (Biodesigner II, III) Responsibilities: Perform massively parallel reporter assays and high-throughput screens across diverse cellular contexts using cellular and molecular readouts. Develop and execute molecular biology workflows such as vector design and cloning, DNA/RNA extraction, RT-PCR, qPCR, and next-generation sequencing. Support cell culture activities and experiments in multiple cell lines, at small and large scales. Design and execute cell-based assays (AAV/lentiviral transduction, transfection, flow cytometry, immunostaining, and other plate reader assays). Engineer and characterize cell-based systems using synthetic biology tools and techniques. Conduct and troubleshoot experiments, independently and in collaboration with colleagues, to optimize screening throughput, sensitivity, and specificity. Proactively troubleshoot technical issues and recommend potential corrective actions based on personal observations and literature searches. Prepare summaries of data and present internally to colleagues and management. Draft SOPs, follow protocols, diligently document experimental data in lab notebooks, and organize and maintain electronic work records. Author scientific reports and data summaries. Collaborate with cross-functional teams to meet project goals, bridging early discovery with high-throughput screens to nominate and optimize candidates for further characterization. Qualifications: Bachelor's or Master's degree in Biology, Biochemistry, Chemical Engineering, Biological Engineering, or a related field. At least 2 years of industry wet lab experience. Mammalian cell culture experience (culturing, transfecting and transducing cells, and DNA/RNA purification from cells). Molecular biology expertise (vector design and cloning, qPCR, primer and probe design, DNA/RNA extraction workflows) Critical thinker with excellent communication skills who thrives in a multidisciplinary, fast-paced team environment. Strong written and verbal communication skills. Preference will be given to those who display: High throughput screening assay development in an industry setting. High motivation, with a strong work ethic and dedication to generating impact. Attention to detail, with the ability to extract deep insights from data. First-principles thinking, and an ability to refine one's intuition based on additional data. Ability to go from ideation to data in an independent fashion. Long-term personal vision with defined career goals. High EQ with team-oriented thinking. Experience with pooled, high-throughput screens using next-generation sequencing-based readouts, and/or preparing screening plasmid libraries from synthesized oligo arrays. Experience with CRISPR-Cas systems and/or gene editing and delivery technologies. Experience preparing next-generation sequencing libraries (Illumina, PacBio, and/or Nanopore platforms). If you have a passion for advancing gene editing technologies and desire to be part of a pioneering biotech company, we encourage you to apply and join our ambitious team. Please apply directly through LinkedIn. Amber Bio is an equal-opportunity employer and encourages applications from candidates of diverse backgrounds. We value diversity and are committed to creating an inclusive and supportive work environment for all employees.