Graduate research assistant jobs in Novato, CA - 1,618 jobs

### As a research scientist with Martian, you will develop new techniques to understand how AI models work. This work will focus on exploring and improving a technique we call “model mapping”: converting transformers into more interpretable representations (such as programs). We are looking for people who can develop and scale up methods for making transformers more interpretable through model mapping and then understanding the transformers in the new domain we map to. Full details can be found here. #J-18808-Ljbffr

A leading AI technology company in San Francisco is seeking a Research Scientist to advance AI models and techniques. You'll work in a collaborative environment, focusing on novel research, and applying AI solutions to real-world challenges. Candidates with a Bachelor's or Master's degree and 2+ years of relevant experience are encouraged to apply, with a competitive salary range of $192,000 - $260,000. #J-18808-Ljbffr

About Nudge Nudge's goal is to help the brain work better by creating a generalized product that can precisely stimulate and image the brain, entirely non-invasively. We aim to achieve this by developing cutting-edge ultrasound technology to treat neurological and psychiatric disorders, like addiction, and eventually, creating a mainstream consumer device that can modulate mood, focus, sleep, and more. To realize those ambitions, we're growing a scrappy, multidisciplinary, science and engineering team focused on making the best technology possible for interfacing with the whole brain, and a product that has the potential to improve people's daily lives more than any other. About the team The Research Team at Nudge is innovating on multiple frontiers in neuroscience and neurotechnology, and is primarily focused on developing ultrasound-based neuromodulation to treat conditions like depression, chronic pain and addiction as well as enhance the wellbeing of healthy people. We're also building the first scalable, portable hardware for noninvasive structural ultrasound-based imaging the quality of an MRI. The team is running human trials for neuromodulation and developing algorithms that will enable on-device imaging. About the role Work closely with the Head of Research and engineering team to build the capabilities for on-device ultrasound-based imaging. Develop algorithms for structural and functional ultrasound-based imaging Perform validation of in-silico ultrasound imaging methods with Nudge hardware in physical models and in vivo Contribute to the development of aberration correction techniques informed by ultrasound-based imaging About you 5+ years experience PhD or Postdoc in Bioengineering, Medical Imaging, Physics or equivalent Expertise in ultrasound physics and metrology Demonstrated history of exceptional contributions in your prior work experiences Expertise in one or more of: Full-waveform inversion imaging Functional transcranial doppler imaging Functional ultrasound imaging Machine learning experience a plus Compensation $140,000 - $230,000/year + equity Your salary may vary depending on multiple factors such as job-related knowledge, skills, and experience. #J-18808-Ljbffr

A cutting-edge robotics startup is looking for a Research Scientist to enhance their robotic manipulation systems. This role entails advancing research, collaborating on publications, and prototyping solutions within a multi-disciplinary team. The ideal candidate has a strong grasp of modern robotic methods and 5+ years of relevant experience, alongside a solid publication record in prestigious conferences. Compensation ranges from $160,000 to $210,000 annually, with equity options available. #J-18808-Ljbffr

About the Team The Strategic Deployment team makes frontier models more capable, reliable, and aligned to transform high-impact domains. On one hand, this involves deploying models in real-world, high-stakes settings to drive AI-driven transformation and elicit insights-training data, evaluation methods, and techniques-to shape our frontier model development. On the other hand, we leverage these learnings to build the science and engineering of impactful frontier model deployment. As a key element of this effort, OpenAI for Science aims to harness AI to accelerate the process of scientific research. This involves building models and an AI-powered platform that speeds up discovery and helps researchers everywhere do more, faster. About the Role As a Research Scientist focused on the mathematical sciences, you will help build models, tools, and workflows that move theoretical research-in fields such as mathematics, theoretical physics, and theoretical computer science-forward. You\'ll design domain-specific data and signals, shape training and evaluation, guide how to wire models to scientific tools, and work with the academic community to speed up adoption and impact. We\'re looking for people who... Hold a current or recent academic position in mathematical sciences (mathematics, theoretical physics, theoretical computer science) or a related field Regularly use frontier models in their own research Move easily between theory and code, and are eager to contribute technically as well as academically Either know or are eager to learn modern AI and run AI experiments end-to-end Are strong scientific communicators Care about rigor and reproducibility in scientific results This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Assist in designing and building frontier AI models that are great at solving frontier mathematical sciences problems Build high-quality scientific datasets and synthetic data pipelines (symbolic, numeric, and simulator-based) Design reinforcement and grading signals for physics and run reinforcement learning/optimization loops to improve model reasoning Define and run evals for scientific reasoning, derivations, simulations, and literature grounding; track progress over time Partner with research labs and the academic community Drive adoption of frontier AI within the scientific community Uphold high standards for safety, data governance, and reproducibility You might thrive in this role if you Are passionate about pushing the boundaries of your field using AI Have used ChatGPT to do calculations and prove or improve lemmas in your field of study Communicate clearly to both scientists and AI engineers; you like collaborating across teams and with academia Nice to have Open-source contributions to mathematical science or AI tooling Experience building or curating domain datasets and benchmarks Experience engaging a research community (teaching, workshops, tutorials, standards) About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI\'s Affirmative Action and Equal Employment Opportunity Policy Statement. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology. Compensation Range: $380K - $460K #J-18808-Ljbffr

Substrate is addressing one of the most important technological problems facing the United States. At the intersection of advanced manufacturing and cutting‑edge physics, we are developing technologies that will reshape the semiconductor industry and strengthen America's technological leadership. We are a team of world‑class scientists, engineers, and technical experts building technology for the United States. Summary As a Research Scientist working with AI, you will accelerate and augment R&D workflows by applying machine learning to scientific simulations and modeling while simultaneously building internal AI capabilities across the organization. This role sits at the intersection of cutting‑edge physics and artificial intelligence, and you'll work hands‑on to develop AI‑augmented tools that enable breakthrough research, and build the infrastructure and expertise that empowers our technical teams to leverage AI in their own work. Whether you are a physicist who has embraced machine learning or an AI expert with deep scientific domain knowledge, you will play a pivotal role in defining how we utilize AI to accelerate our own internal R&D. Responsibilities Integrate machine learning techniques to accelerate scientific simulations, modeling, and computational workflows Develop AI‑augmented tools for materials science, device physics, or accelerator physics applications Build internal AI infrastructure and capabilities to enable research teams across the organization Train and mentor scientists and engineers on integrating AI/ML into their research workflows Implement surrogate models, physics‑informed neural networks, or generative approaches for scientific problems Develop data pipelines and frameworks for scientific machine learning across distributed teams Collaborate with computational physicists and experimentalists to identify high‑impact AI applications Set AI best practices and establish standards for ML‑augmented R&D Required Qualifications 5+ years professional or academic research experience in physical sciences, engineering, or related field 2‑3+ years hands‑on experience applying machine learning to scientific or technical problems Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow, JAX, or similar) Deep understanding of scientific computing, numerical methods, and computational modeling Proven ability to translate scientific problems into machine learning approaches Experience building tools, infrastructure, or capabilities used by technical teams Preferred Qualifications PhD in Physics, Materials Science, Computer Science, Applied Mathematics, or related field Publications applying ML to scientific computing, simulation, or experimental data analysis Experience with physics‑informed machine learning or scientific foundation models Background in accelerator physics, semiconductor devices, materials modeling, or related domains Track record of enabling technical teams through tool development or mentorship Salary Range $150,000-$400,000 USD Substrate is an equal opportunity employer. It provides equal employment opportunity to all applicants without regard to race, color, religion, national origin, disability, medical condition, marital status, sex, gender, age, military or veteran status, or any other characteristic protected by applicable federal, state, or local laws. Substrate will provide reasonable accommodations to applicants with disabilities. If you need an accommodation during the hiring process, please let your recruiter know. Applicants must be legally authorized to work in the United States. This position is not eligible for visa sponsorship. #J-18808-Ljbffr

*To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.*Salesforce Research advances state-of-the-art AI techniques, developing models and prototypes that pave the path for innovative products at Salesforce. We tackle real-world problems in areas such as image recognition and natural language processing from Salesforce's enterprise customers by harnessing the latest deep learning techniques. As part of our team you'll learn unique skills, work with talented people and help us shape the future of AI in Palo Alto and our recently announced new hub, Salesforce Research Asia in Singapore!**Job Category**Software Engineering****Job Details********About Salesforce****Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.**Salesforce AI Research is looking for outstanding AI Research Scientists / Research Engineers.**Our team discovers new research problems, develops novel models, and bridges the gap between groundbreaking theory and customer-facing reality. We are dedicated to a high-impact research model that provides the best of both worlds: the ability to advance the state-of-the-art in AI and the opportunity to see that work operate at massive, real-world scale within the world's #1 AI CRM. We believe that making substantive progress on hard, enterprise-level applications drives and sharpens the research questions we study.Check out our website to learn more about the groundbreaking work of the Salesforce AI Research team:**Candidates have a strong background in one or more of the following areas:*** **Agentic AI & Reasoning:** LLM-powered agents, reinforcement learning, and autonomous workflows.* **Multimodal & Computer Vision:** Vision-language models (VLM), video understanding, and visual grounding for GUI agents.* **Speech Intelligence:** Voice intelligence, TTS/ASR, human-like turn-taking, and low-latency audio processing.* **Efficient Systems:** Scalable deep learning infrastructure, high-performance audio/video pipelines, and low-latency deployment.* **Core Modeling:** Machine learning methodology, pre-training/post-training (RLHF, DPO), and model distillation.**Responsibilities:*** Own and pursue ambitious research and engineering goals aligned with strategic initiatives.* Develop novel models and technical solutions for real-world, large-scale problems within the enterprise ecosystem.* Design, build, and maintain production-ready services, including scalable APIs and agentic evaluators.* Collaborate across a strike-team of researchers and engineers to deliver complex projects that directly impact our core AI products and customer experiences.**Minimum Qualifications:*** Ph.D., Master's, or Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.* A strong publication record in top AI venues (e.g., NeurIPS, ICLR, ICML, CVPR, ICCV, ACL, EMNLP) **OR** a proven track record of shipping AI products to real users.* Demonstrated expertise in one or more core focus areas: LLMs, Agentic Systems, Computer Vision/Multimodal, Speech Intelligence, or Research Engineering.* Experience with Python and deep learning libraries/platforms (e.g., PyTorch, Jax, or DeepSpeed).* Proven ability to implement, operate, and deliver results via innovation at a large scale.**Preferred Qualifications:*** Full-time industry experience in deep learning research and/or product development.* Experience training and evaluating large-scale multimodal models or speech models, including techniques for alignment, safety, and latency optimization.* Experience with production cloud deployments (AWS/GCP), container orchestration (Kubernetes), or high-performance systems (MLOps).* Strong programming skills, with a competitive background (e.g., ACM-ICPC or significant open-source contributions) or experience in UI/graphic design.* Thoughtful about AI impacts, trust, and ethics.* Outstanding communication, collaboration, and problem-solving skills.Unleash Your PotentialWhen you join Salesforce, you'll be limitless in all areas of your life. Our benefits and resources support you to find balance and *be your best*, and our AI agents accelerate your impact so you can *do your best*. Together, we'll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future - but to redefine what's possible - for yourself, for AI, and the world.****Accommodations****If you require assistance due to a disability applying for open positions please submit a request via this .****Posting Statement****Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: ******************************************* to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.### ### At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.The typical base salary range for this position is $114,200 - $306,600 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $137,100 - $334,600 annually.The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.### ### ### ### ### ###Founded in 1999, Salesforce is the global leader in Customer Relationship Management (CRM). Companies of every size and industry are using Salesforce to transform their businesses, across sales, service, marketing, commerce, and more by connecting with customers in a whole new way. We harness technologies that can revolutionize companies, careers, and, hopefully, our world. Salesforce is built on a set of four core values: Trust, Customer Success, Innovation, and Equality. By making technology more accessible, we're helping create a future with greater opportunity and equality for all. This has taken our company to great heights, including being ranked by Fortune as one of the “Most Admired Companies in #J-18808-Ljbffr

We are Genmo, a research lab dedicated to building open, state-of-the-art models for video generation towards unlocking the right brain of AGI. Join us in shaping the future of AI and pushing the boundaries of what's possible in video generation. Key responsibilities Lead research initiatives in advanced diffusion models for text-to-video generation, focusing on improving visual quality, temporal consistency, and semantic fidelity Develop and implement state-of-the-art algorithms for translating textual descriptions into dynamic video content Design and conduct rigorous experiments to validate new ideas and evaluate model performance Collaborate with cross-functional teams to integrate research breakthroughs into our production pipeline Stay at the cutting edge of the field by regularly reviewing academic literature and attending top-tier conferences Contribute to the research community through high-quality publications and open-source contributions Mentor junior researchers and foster a culture of innovation within the research team Work closely with product teams to align research directions with user needs and market opportunities Qualifications Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field Must have: Strong publication record in top-tier conferences (e.g., CVPR, ICCV, NeurIPS, ICML) with a focus on generative models, particularly diffusion models Extensive experience implementing and optimizing large-scale generative models for image or video tasks Deep understanding of state-of-the-art techniques in text-to-image and text-to-video generation Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow Excellent communication skills with the ability to explain complex technical concepts to diverse audiences Proven ability to work collaboratively in a team environment Ideal candidate will have: Postdoctoral or industrial research experience in generative AI for video Hands-on experience with text-to-video generation projects Expertise in other generative model architectures (e.g., GANs, VAEs) and their applications to video Experience working with large-scale datasets and distributed computing environments Track record of successful collaboration with product teams on technology transfers Familiarity with video codecs, compression techniques, and perceptual quality metrics Contributions to open-source projects in the field of generative AI Additional information The role is based in the Bay Area (San Francisco). Candidates are expected to be located near the Bay Area or open to relocation. Genmo is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law. Genmo, Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish. #J-18808-Ljbffr

Machine Learning Research Scientist : Fast-growing AI research startup : As a Machine Learning Research Scientist, you will drive the development of next-generation AI models at a well-funded startup in the heart of San Francisco. You will lead groundbreaking research initiatives, translate complex theoretical concepts into scalable production code, and collaborate with a world-class team to push the boundaries of what is possible in machine intelligence. Location: San Francisco, USA Why this role is remarkable: Opportunity to work on bleeding-edge AI research that directly impacts the core product roadmap Backed by top-tier VCs in an environment that prioritizes technical excellence and rapid experimentation Join a high-caliber team of researchers and engineers from leading global technology institutions What you will do: Design and implement novel machine learning architectures to solve complex, high-dimensional data challenges Conduct rigorous experiments to validate model performance and ensure robustness in real-world applications Collaborate with engineering teams to integrate research breakthroughs into a scalable software ecosystem The ideal candidate: PhD or equivalent research experience in Computer Science, Mathematics, or a related quantitative field Proven track record of publishing at top-tier AI conferences such as NeurIPS, ICML, or ICLR Proficiency in deep learning frameworks like PyTorch or TensorFlow and strong software engineering fundamentals Next steps Step 1. Visit our website. Step 2. Click Talk to Jack. Step 3. Talk to Jack so he can understand your experience and ambitions. Step 4. Jack will make sure Jill (the AI agent working for the company) considers you for this role. Step 5. If Jill thinks you're a great fit and her client wants to meet you, they will make the introduction. Step 6. If not, Jack will find you excellent alternatives. All for free. We never post fake jobs This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network. Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description. We appreciate this can make them look a bit suspect, but there isn't much we can do about it. Give Jack a spin! You could land this role. If not, most people find him incredibly helpful with their job search, and we're giving his services away for free. #J-18808-Ljbffr

About Sygaldry Sygaldry Technologies is building quantum-accelerated AI servers to exponentially speed up training and inference for AI. By integrating quantum and AI, we're accelerating the path to superintelligence, and engineering the conditions for it to scale efficiently and operate affordably. Sygaldry AI servers combine multiple qubit types within a single, fault-tolerant architecture to deliver the combination of cost, scale, and speed necessary for advanced AI applications. We pioneer new domains in physics, engineering, and AI, tackling the hardest challenges with a grounded, optimistic, and rigorous culture. We're looking for individuals ready to define the intersection of quantum and AI and drive its profound global impact. About the Role Generative AI is transforming what's computationally possible-but it's also exposing the limits of classical hardware. Diffusion models produce extraordinary results, yet their iterative sampling and high-dimensional score estimation create computational bottlenecks that scale poorly. We believe quantum computing offers a path through these bottlenecks. As an ML Research Scientist, you'll work at the frontier of generative modeling and quantum acceleration, developing the theoretical foundations and practical implementations that connect these fields. You'll identify where quantum approaches can provide genuine advantage in generative workflows-not incremental improvements, but structural speedups rooted in the mathematics of these models. What You'll Work On Generative Model Architecture & Efficiency Advance state-of-the-art diffusion and score-based generative models Analyze computational bottlenecks in sampling, denoising, and likelihood estimation Develop and benchmark novel solver methods for diffusion ODEs/SDEs Quantum-Classical Integration Identify mathematical structures in generative models amenable to quantum speedup Prototype hybrid workflows where quantum subroutines accelerate classical pipelines Rigorously benchmark theoretical versus practical advantage in realistic workloads Research to Production Translate research insights into scalable implementations Collaborate with quantum hardware teams to inform architecture requirements Build systems that make quantum-accelerated generation accessible to practitioners You May Be a Good Fit If You Have deep expertise in diffusion probabilistic models, score matching, or related generative methods Understand the mathematical foundations: SDEs, ODEs, Langevin dynamics, probability flow Are experienced with ML frameworks (PyTorch, JAX) and efficient inference implementation Question assumptions and validate with rigor, following interesting threads wherever they lead Communicate complex ideas clearly across research communities Are excited to work on problems no one has solved before Strong Candidates May Have Published research on diffusion models, score-based generation, or neural ODE/SDE methods Experience optimizing sampling efficiency (DDIM, DPM-Solver, consistency models, etc.) Familiarity with numerical methods for differential equations Understanding of quantum algorithms and computational complexity Background in high-dimensional probability or stochastic processes Why This Matters Your work accelerates the path to quantum superintelligence. Each quantum component integrated, each AI model enhanced, each instruction set optimized brings us closer to a future where intelligence and quantum mechanics are inextricably intertwined. We're not building incremental improvements - we're creating exponential transformations that will make AI more affordable, sustainable, personalized, and fundamentally more capable. How We're Different We're building the infrastructure for quantum superintelligence and pioneering new domains at the intersection of physics, engineering, and AI. At Sygaldry, curiosity and intellectual courage drive our work. We approach ambitious challenges with a grounded, optimistic, and rigorous culture and know that kind people build the strongest teams. We prioritize mission over ego and collaborate openly with a strong sense of shared purpose. We dream big, yet we execute with a love of detail. We're looking for scientists, engineers, and operators to forge new paths with us at the intersection of quantum and AI. Culture & Benefits Visa Sponsorship - We know what it takes to make top talent thrive here. We're open to supporting visas whenever possible. Compensation - We value your contribution and invest in your future with a competitive salary and meaningful equity. Benefits - Your well-being matters. We provide company-sponsored health coverage to give you and your family peace of mind. Connection - Whether it's company offsite or casual crew socials, we make time to connect, recharge, and have fun together. Time Off - We trust you to take the time you need. Unlimited PTO so you can rest, recharge, and come back ready to make an impact. We encourage applications from candidates with diverse backgrounds. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. We encourage you to apply even if you do not believe you meet every single qualification. If you don't think this role is right for you, but you believe that you would have something meaningful to to contribute to our mission, please reach out at ********************** #J-18808-Ljbffr

Granica is an AI research and infrastructure company building reliable and steerable representations for enterprise structured data. The rarest thing in enterprise AI is durable access plus trust. Crunch is how we earn it: a policy-driven physical health layer that keeps large tabular data estates efficient and reliable, safely and reversibly. On top of that foundation, we're building structured intelligence using Large Tabular Models: systems that learn cross-column and relational structure to deliver trustworthy answers and automation with provenance and governance built in. The Mission AI today is limited not only by model design but by the inefficiency of the data that feeds it. At scale, each redundant byte, each poorly organized dataset, and each inefficient data path slows progress and compounds into enormous cost, latency, and energy waste. Granica's mission is to remove that inefficiency. We combine new research in information theory, probabilistic modeling, and distributed systems to design self-optimizing data infrastructure: systems that continuously improve how information is represented and used by AI. Granica's Research group led by Prof. Andrea Montanari (Stanford), bridging advances in information theory and learning efficiency with large-scale distributed systems. Together, we share a conviction that the next leap in AI will come from breakthroughs in efficient systems, not just larger models. Granica is pioneering a new class of structured AI models: foundational models built to learn and reason from the world's relational, tabular, and structured data. While others focus on unstructured text or media, we are exploring the next frontier: systems that understand and reason over the information that runs the global economy. What You'll Build and Research Invent and prototype algorithms that define the foundations of structured AI, advancing representation learning and efficient information modeling for enterprise and tabular data at petabyte scale. Develop adaptive learners that fuse statistical learning theory with large-scale systems optimization, contributing to a new generation of foundational models for structured information. Design architectures that integrate symbolic, relational, and neural components, enabling AI systems to reason directly over structured enterprise data. Build cost models and optimization frameworks that make structured learning efficient, both computationally and economically. Collaborate closely with the Granica Research group led by Prof. Andrea Montanari (Stanford) and with systems engineers to transform theoretical ideas into production-grade systems used across live enterprise workloads. Iterate fast: prototype new model architectures, evaluate on live datasets, and publish results that advance both theory and practice. Contribute to the global research community shaping the future of structured AI and efficient learning. What You'll Bring Ph #J-18808-Ljbffr

Join our core R&D team building end-to-end automated research systems. 📰 The 1st fully AI-generated scientific discovery to pass the highest level of peer review - the main track of an A* conference (ACL 2025). ************************************** Key Responsibilities Design & implement novel architectures for automated research. Collaborate with a focused group of researchers tackling problems at the forefront of long‑horizon agentic capabilities, post‑training for open‑ended goals, and environment development. Publish internal key‑findings along with external collaboration success stories. Qualifications PhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Exceptional candidates with strong research contributions are encouraged to apply regardless of formal degree. Proven track‑record of high‑impact AI/ML research contributions in either the academic or corporate settings. Expertise in developing long horizon. multi‑agent systems and/or model post‑training, with a focus on capabilities. Even better if built for scientific domains and/or open‑ended discovery purposes. Passion for accelerating the process of problem‑solving & scientific discovery, with comfort in high‑autonomy roles & environments. Our Culture Competitive salary & equity packages. Unlimited PTO with a focus on on‑site team‑building & communal work environment. Conference attendance & involvement in community‑facing events. High‑agency & responsibility. #1: We are a small, dedicated group of top investors, researchers, and industry veterans, dedicated to the mission of accelerating discovery. Join us. #J-18808-Ljbffr

Virtue AI is at the forefront of AI security & compliance. Our mission is to build the essential AI security platform with advanced and comprehensive guardrails and red‑teaming tools that enable organizations to deploy different AI applications confidently and responsibly in different sectors, such as finance, healthcare, telecom, retail, and government. Just as Palo Alto Networks redefined network security, our mission is to define and lead the new category of AI Security. We are a well‑funded, early‑stage startup founded by industry veterans, and we're looking for passionate builders to join our core team. Are you a high‑performing, motivated machine learning engineer ready to make a significant impact in the AI security space? We are looking for talented engineers to develop cutting‑edge products on agent and LLM securities. What You'll Do As a Research Scientist, you will play a key role in developing production‑ready and cutting‑edge agent and ML security techniques. Your work will directly contribute to advancing our products and services and driving innovation within the industry. You will: Develop our core techniques for agent and model red‑teaming, including discovering novel testing paths, designing novel testing techniques, and developing automatic testing platforms Develop and train our core guardrail models for different input modalities and defense targets and goals Apply efficiency inference methods to reduce model latency Work with the research engineers to integrate our developed techniques into products What Makes You a Great Fit You'll thrive in this role if you're excited by new technology, love solving customer problems, and can comfortably bridge the business and technical worlds. Required qualifications: Proficiency in programming languages such as Python, along with expertise in LLM libraries like PyTorch, DeepSpeed, OpenRLHF, vLLM, verl, etc Experience in LLM finetuning for different modalities Experience in building LLM‑based agents for various applications Experience in conducting large‑scale red‑teaming for LLMs and agents Preferred qualifications: Hands‑on experience with Docker for containerization and deployment Hands‑on experience in backend engineering (Go, C/C++) and front‑end development (Node.js, Typescript) Enthusiasm for thriving in a fast‑paced startup environment Strong problem‑solving skills and effective communication abilities Why Join Virtue AI Competitive base salary compensation + equity commensurate with skills and experience. Impact at scale - Help define the category AI security and partner with Fortune 500 enterprises on their most strategic AI initiatives. Work on the frontier - Engage with bleeding‑edge AI/ML and deploy AI security solutions for use cases that don't yet exist anywhere else yet. Collaborative culture - Join a team of builders, problem‑solvers, and innovators who are mission‑driven and collaborative. Opportunity for growth - Shape not only our customer engagements, but also the processes and culture of an early lean team with plans for scale. Equal Opportunity Employment Virtue AI is an Equal Opportunity Employer. We welcome and celebrate diversity and are committed to creating an inclusive workplace for all employees. Employment decisions are made without regard to race, color, religion, sex, gender identity or expression, sexual orientation, marital status, national origin, ancestry, age, disability, medical condition, veteran status, or any other status protected by law. We also provide reasonable accommodations for applicants and employees with disabilities or sincerely held religious beliefs, consistent with legal requirements. #J-18808-Ljbffr

AI Researcher ai Hum.ai is building planetary superintelligence. Backed by top funds, we've raised $10M+ and are now heads down building. Join us at the cutting edge, where we're scaling generative transformer diffusion models, designing next-gen benchmarks, and engineering foundation models that go far beyond LLMs. You'll be at the core of a moonshot journey to define what's next in agentic AI and frontier model capabilities. We are looking for an experienced AI Researcher who is eager to advance the frontier of AI, help us design, build, and scale end-to-end novel foundation models, and leverage their hands‑on experience implementing a wide range of pre‑training and post‑training models, including large foundation models (beyond just LLM fine‑tuning). Who are we? Hum is a seed‑funded startup on a mission to create positive impact through earth observation and AI. Founded at the University of Waterloo by a team of PhDs and engineers, we're backed by some of the best AI and climate tech investors like HF0, Inovia Capital and Propeller Ventures, angels like James Tamplin (cofounder Firebase) and Sid Gorham (cofounder OpenTable, Granular), and partners like Amazon AWS and the United Nations. What do we do? We're building multimodal foundation models for the natural world. We believe there's more to the world than the internet + more to intelligence than memorizing the internet. Our models are trained on satellite remote sensing and real‑world ground truth data, and are used by our customers in nature conservation, carbon dioxide removal, and government to protect and positively impact our increasingly changing world. Our ultimate goal is to build AGI of the natural world. The role will involve: Research & Design: Deep understanding of current machine learning research. Proven track record of generating new ideas or enhancing existing ones in machine learning, evidenced by first‑author publications or projects. Contribute to research that uncovers the semantics of large datasets, with a focus on earth observation and remote sensing data. Ability to independently manage and execute a research agenda, selecting impactful problems and conducting long‑term projects autonomously. Implementation: Developing high‑level proof‑of‑concept (POC) models. Experimenting with new state‑of‑the‑art techniques to surpass existing models. Plan and execute innovative research and development to push the boundaries of current technology. Writing and Publication: Assisting in the preparation and writing of technical and scientific papers for publication. Demonstrated strong scientific communication/presentation skills. Requirements PhD degree in computer science, engineering, a related field, or equivalent experience. Proven track record of successful machine learning research projects. 5+ years of experience in relevant jobs. Strong scientific understanding of the field of generative AI. Location wise, strong preference for in‑person in San Francisco. We are an entirely in‑person team, but are willing to consider remote for exceptional candidates. Nice to have Proficiency in scripting languages such as Python, Bash, or PowerShell. Demonstrated experience with deep learning and transformer models. Familiarity with designing, training, and fine‑tuning large models. Proficiency in frameworks like PyTorch or TensorFlow. Strong technical engineering skills. Previous experience in creating high‑performance implementations of deep learning algorithms. Team player, willing to undertake various tasks to support the team. #J-18808-Ljbffr

A multi-modal foundational AI company is seeking a Foundational AI Research Scientist to lead research on large-language-model architectures. The role involves designing and validating new transformer variants and attention mechanisms for production systems. Ideal candidates will have a Ph.D. and 3+ years of industry experience in AI research, with deep knowledge of sequence modeling architectures and pre-training of large models. The position offers a competitive salary, flexible PTO, and comprehensive benefits. #J-18808-Ljbffr

A leading AI technology firm in San Francisco seeks an ML Sys Research Engineer to optimize algorithms for their next-generation Agent RL training platform. The role involves building and profiling frameworks, post-training state-of-the-art models, and collaborating with teams. Ideal candidates should have LLM training experience, strong software engineering skills, and a relevant advanced degree. Competitive compensation and benefits package offered. #J-18808-Ljbffr

The Center for Brain and Health (CBH) at New York University Abu Dhabi (NYUAD) is seeking a Research Scientist to explore scientific questions related to an in-progress normative brain database. The research scientist will be a key member of a multidisciplinary team responsible for collection of multimodal brain data, including MR imaging, MEG, EEG, and eye tracking. The tentpole of the CBH is the first normative brain database in the region, featuring structural, functional, diffusion MRI, behavioral and health measures, genetic information, and lifestyle questionnaires. The anticipated appointment start date is May 1, 2026, with a guaranteed term of 18 months and the possibility of renewal based on performance. Responsibilities Explore scientific questions related to the normative brain database. Conduct data collection and processing of multimodal MR imaging, MEG, EEG, and eye tracking. Apply big‑data analysis techniques and advanced computational methods to brain imaging data. Collaborate with the multidisciplinary research team. Contribute to peer‑reviewed publications and scientific communication. Qualifications Ph.D. in Neuroscience, Psychology, MR Physics, Data Science, Computer Science, or a related field. Postdoctoral experience or an equivalent level of experience preferred. Extensive experience with multimodal MRI, including functional, structural, and tractography methods. Proficiency in big‑data analysis techniques. Experience with other large brain databases preferred. Strong computational skills and a solid publication record. Benefits Competitive salary and benefits. Housing allowance. Other benefits as specified in the employment terms. Application Instructions Cover letter. Curriculum vitae with a full publication list. Transcript. Statement of research interests. Three representative publications. Three letters of reference. All materials must be submitted in PDF format. Applications are accepted immediately; please submit through the NYUAD careers page at ************************************************************* For questions, contact ************** or **************************. UAE nationals are encouraged to apply. Equal Employment Opportunity Statement NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels. Sustainability Statement NYU aims to be among the greenest urban campuses in the country and achieve carbon neutrality by 2040. Learn more at nyu.edu/sustainability. #J-18808-Ljbffr

A pioneering technology firm is looking for a high-performing individual to advance molecular machine learning using deep learning architectures. You will architect and integrate state-of-the-art models, optimize performance from code to hardware, and collaborate with scientists to develop innovations for drug discovery and material sciences. The role requires expertise in frameworks like PyTorch and JAX, deep understanding of GPU optimizations, and a passion for tackling challenging technical problems. #J-18808-Ljbffr

The LLM Data Company (YC X25) provides post-training data and RL environments to foundation model labs and frontier applied AI companies. We have raised $3.6m from Tier 1 VCs and are growing 200%+ month-over-month. Responsibilities Design and implement scalable RL recipes for post-training task-specific models Develop modular environments, reward functions, and evaluator scaffolds for internal and customer-facing tasks Drive research at the intersection of scalable infra and modern RL frameworks to enable RL-as-a-service Drive foundational research to publish open source environments and training data Build data generation and curation pipelines to support frontier post-training Collaborate with product teams to deliver a user friendly interface for non-technical users to generate data Qualifications Bachelor or Master in Computer Science or related field Comfort with core tooling (verl, PyTorch, etc.) Familiarity with modern post-training techniques (GRPO, etc.) Experience with evaluations and reward engineering Published in top journals (ICLR, NeurIPS, ICML, etc.) Why you should join Cutting-edge research: Work on unpublished, novel training environments Direct lab exposure: Projects that labs actually use and validate in production High autonomy: Wide design space to propose and run experiments with minimal oversight Early team member: Join as one of the first 10 people with significant equity upside #J-18808-Ljbffr