Graduate research assistant jobs in Palo Alto, CA - 3,064 jobs

Sentra is building organizational superintelligence through memory infrastructure that reasons across time, causality, and context. As a Research Scientist, you will tackle fundamental problems in knowledge representation, temporal reasoning, and semantic compression. You will design and implement systems that maintain execution state for entire organizations, consolidate millions of micro-events into durable knowledge, and learn patterns that predict events before it happens. Key Responsibilities Build LLM-powered information extraction pipelines that process unstructured communications and text data into structured entity-relationship representations. Develop memory consolidation algorithms that validate information through multiple observations, merge duplicate entities, and prune ephemeral data. Design temporal knowledge graph architectures that model organizational execution state as living, continuously updated systems rather than static records. Create graph attention mechanisms and reasoning systems for complex causal queries about blockers, dependencies, and outcome patterns. Research lossy semantic compression using information-theoretic principles to condense event streams into query-relevant long-term memory. Design entity resolution systems handling identity evolution where entities merge, split, and transform through time. Build meta-learning systems that identify organizational patterns and recognize when current situations match historical success or failure indicators. Develop privacy-preserving cross-organizational learning using federated learning and differential privacy techniques. Publish research findings and contribute to the broader research community on knowledge graphs and organizational intelligence. Must-have Requirements 5+ years building novel systems in machine learning, NLP, knowledge graphs, or related areas with evidence through publications, production implementations, or significant open-source contributions. Deep knowledge of knowledge graphs, graph neural networks, or temporal reasoning demonstrated through shipped systems and architectural exploration. Strong ML and NLP foundation, particularly in information extraction, entity resolution, or semantic representation. Proficiency in Python and modern ML frameworks (PyTorch preferred) with experience deploying models at scale. Track record of publishing research (conference papers, technical blog posts, or detailed technical documentation) and exploring novel architectures. Ability to move between theoretical investigation and practical implementation, shipping research into production. Bonus skills: Graph databases (Neo4j, TigerGraph, Neptune) and query optimization for large-scale graphs. Information theory, compression, or temporal data structures. Causal inference, probabilistic reasoning, or Bayesian methods. Distributed systems, stream processing, or real-time ML serving. Human memory and cognition models. Privacy-preserving ML (federated learning, differential privacy, secure multi-party computation). Enterprise AI systems, workflow automation, or organizational software. Publications at top-tier conferences (NeurIPS, ICML, ICLR, KDD, EMNLP, ACL, WWW, SOSP, OSDI). Compensation and Benefits Base Salary: $150,000 - $300,000 Equity: 0.3% - 2% depending on level Comprehensive Health Coverage: Medical, dental, and vision Wellness & Productivity Stipend: $2,500/month to cover meals, transport, gym memberships, or other personal productivity needs Hardware & Tools: Latest MacBook Pro and AI development tools (ChatGPT Pro, Claude Pro, Cursor, etc.) Learning & Growth: Dedicated budget for conferences, courses, and professional development Relocation Support: Available for on-site hires Flexible Time Off Policy Total estimated annual benefits package: ~$30K-$35K in addition to base and equity. #J-18808-Ljbffr

### 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

Nimble is an AI robotics company building the autonomous supply chain to enable fast, efficient, and sustainable commerce. We're developing a general-purpose robot AI and a warehouse generalist superhumanoid robot, the first robot in the world capable of performing all core warehouse functions. We recently closed a $106M Series C at a $1B valuation, and we are continuing to grow our world‑class team. Mission: to empower and inspire mankind to accomplish legendary feats by inventing robots that liberate us from the menial. Vision: invent the Autonomous Supply Chain - everything from the inside of factories and warehouses to your front door - powered by industry‑generalist superhumanoids to deliver faster, more efficient, and more sustainable commerce. Our founding team comes from the AI labs at Stanford and Carnegie Mellon and our board of directors include famed robotics and AI legends including Marc Raibert (founder of Boston Dynamics), Sebastian Thrun (founder of GoogleX, Waymo; Stanford Professor and considered the father of autonomous vehicles) and Fei‑Fei Li (Chief Scientist of AI at Google and Director of Stanford's AI Lab). Join us and leave your mark on the future of robotics, AI, and global commerce. Why Join Nimble? At Nimble, we are committed to building legendary products, a legendary team, and a legendary legacy. Join us and become part of an ambitious, humble, and resourceful culture where your work will leave a lasting impact on the future of robotics and commerce. Nimble's Core Values: Be relentlessly resourceful - Challenge conventions and overcome obstacles. Be legendary - Be the very best and do work that inspires. Be humble - Prioritize growth, learning, and doing whatever is needed to further the mission. Be dependable - Take ownership and deliver with high agency. The Role Nimble is looking for an AI Robotics Research Scientist to help us advance our robotics moonshot by designing, developing, training, and implementing robotic foundation models, Vision‑Language‑Action Models, general‑purpose robotic AI models, and reinforcement learning algorithms controlling multi‑agent robot fleets. You will play a critical role in working with our all‑star cross‑functional team to build models with immediate applications for the world's biggest robotics opportunity. Responsibilities Develop and train diffusion policies, VLMs, multi‑agent deep RL policies and more Develop data collection pipelines Design data annotation and labeling Support implementation of models into production systems Qualifications P.h.D in Robotics or Computer Science Experience training deep learning models for robotic manipulation or mobility Experience working with real robotic hardware Experience training models in simulation and developing simulation environments Experience collecting custom datasets Experience training on open‑source datasets Strong track record of publishing papers and/or deploying real‑world applications Experience with system architecture, design and development Additional Requirements Must be able to work extended hours and weekends as needed Must be able to work in San Francisco $180,000 - $250,000 a year The above range is the salary range. This position will also receive generous equity for this position. Culture We embrace challenges and strive to make the impossible possible each day. We're not in this to do what's easy or to be mediocre. We want to create something legendary and leave our mark on the world. We're ambitious, we're gritty, we're humble and we're relentlessly resourceful in pursuit of our goals. If this sounds like you then you might be a great fit! Nimble Robotics, Inc. is an equal opportunity employer. We make all employment decisions based solely on merit. We provide equal employment opportunity to all applicants and employees without discrimination on the basis of race, color, religion, national origin, ancestry, disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, sexual orientation, age, military or veteran status, or any other characteristic protected by applicable state, federal or local laws. Nimble's Benefits Paid Time Off Enjoy the time you need to travel, rejuvenate, and connect with friends and family. Health Insurance Nimble provides medical, dental, and vision insurance through several premier plans and options to support you and your family. Paid Parental Leave Enjoy paid bonding time following a birth. Commuter Benefits Take the stress out of commuting with access to fully-paid parking spots. Referral Bonus Get a cash bonus for any friend or colleague that you refer to us that we end up hiring. 401k Contribute towards a 401k for retirement planning. Equity Be an owner in Nimble through our equity program. #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

The Basic Life Research Scientist at Stanford University conducts advanced experimental and computational research to study protein-RNA interactions at scale, integrating high-throughput sequencing with machine learning methods. This role involves designing and optimizing experimental protocols, analyzing data, preparing scientific reports, and mentoring junior lab members within a collaborative and inclusive environment. The position contributes to innovative genomic research with the goal of advancing knowledge in molecular biology and improving human health outcomes. The Department of Genetics at Stanford University is a leading center for genomic research, dedicated to understanding the molecular mechanisms underlying human health and disease. Our department brings together world-class faculty and researchers who develop and employ cutting-edge technologies -from molecular to computational approaches- to tackle fundamental questions in genetics. We foster a collaborative, interdisciplinary environment that bridges basic science with clinical applications, training the next generation of geneticists while pursuing discoveries that translate into improved human health outcomes. Our mission emphasizes scientific excellence, innovation, and the responsible application of genetic knowledge to benefit society. We are committed to building an inclusive scientific community that values the contributions of all our members to our research programs. The Cox laboratory at Stanford University School of Medicine seeks a full-time staff research scientist to accelerate the development of novel technologies for probing protein-RNA interactions at scale. Our laboratory aims to solve the fundamental challenge of predicting protein-RNA complex structures directly from sequence by integrating high-throughput experimental data with machine learning methods. The successful candidate will focus primarily on developing and implementing the experimental technologies that enable these large-scale measurements. More information about the lab can be . In this role, you will perform professional research in support of our scientific mission. You will contribute to developing research goals for the laboratory, work collaboratively with the Lab Head to determine optimal research methods, and independently perform scientific procedures requiring professional judgment. Additional responsibilities include interpreting experimental results, reviewing pertinent literature, and preparing research reports for presentation and publication. What we provide: Basic science research projects with potential for broad and sustained impact on pressing biomedical problems Training in cutting-edge experimental and computational methods in molecular biology and biochemistry, including high-throughput sequencing A collaborative, inclusive, and supportive research environment Opportunities for authorship on research publications A team committed to continuous learning and scientific collaboration Membership in Stanford's vibrant scientific communities across the Department of Genetics, School of Medicine, and broader university CORE DUTIES: Research & Technical Development: Design, develop, and perform specialized experimental procedures for protein-RNA interaction studies, including high-throughput sequencing-based assays Identify methodological challenges in research protocols and implement innovative solutions to optimize experimental outcomes Evaluate emerging technologies and lead the integration of new methodologies into laboratory workflows Troubleshoot complex experimental systems and maintain laboratory instrumentation Organize experimental data Data Analysis & Reporting: • Prepare comprehensive research reports, manuscripts, and presentations for scientific meetings and publication • Collaborate on data visualization and statistical analysis to support research conclusions Laboratory Leadership & Management: Develop and implement short- and long-term research strategies in collaboration with the Lab Head Train and mentor junior laboratory members in experimental techniques and data analysis methods Oversee laboratory operations including supply management, equipment maintenance, and safety protocols Prepare specifications for specialized equipment and coordinate procurement of some research supplies Required Qualifications: Ph.D. in biochemistry, molecular biology, structural biology, genetics, or related field; or equivalent combination of education and experience Demonstrated experience with protein purification, nucleic acid biochemistry, and next-generation sequencing technologies Strong technical proficiency combined with scientific creativity and collaborative skills Ability to work independently while contributing effectively to team-based research goals Ability to develop innovative processes to achieve goals. Directs others to develop essential tasks. Reviews work activities to determine where new information could improve processes or move projects forward Ability to write and prepare reports or manuscripts for presentation to large audiences. Experience mentoring and training junior researchers Commitment to fostering an inclusive and collaborative research environment Preferred Qualifications: Experience with biochemical assays for protein-nucleic acid interactions Familiarity with computational analysis of next-generation DNA sequencing data Prior experience in technology development or method optimization Track record of scientific publications in peer-reviewed journals Physical Requirements: Remaining in a normal seated or standing position for extended periods of time; reaching and grasping by extending hand(s) or arm(s); dexterity to manipulate objects with fingers, for example using a keyboard; communication skills using the spoken word; ability to see and hear within normal parameters; ability to move about workspace. The position requires mobility, including the ability to move materials weighing up to several pounds (such as a laptop computer or tablet). Please Note: • This job description sets forth the job's principal duties, responsibilities, and requirements; it should not be construed as an exhaustive statement, however. • Interested applicants should submit a cover letter, current CV, publication list and the contact information for at least 3 references with their application. The expected pay range for this position is $75,000 to $96,000 per annum. Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years since their applicable education, field or discipline; departmental budget availability; internal equity; among other factors. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University's research mission. Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years since their applicable education, field or discipline; departmental budget availability; internal equity; among other factors. Keywords: protein-RNA interaction, genomic research, high-throughput sequencing, molecular biology, machine learning, biochemistry, structural biology, experimental design, data analysis, scientific publication

By applying to this role, you will be considered for Research Scientist roles across all teams at OpenAI. About The Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We Expect You To Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Be excited about OpenAI's approach to research. Nice To Have Interested in and thoughtful about the impacts of AI technology. Past experience in creating high-performance implementations of deep learning algorithms. 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 do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status. #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

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

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

About Hedra Hedra is a pioneering generative media company backed by top investors at Index, A16Z, and Abstract Ventures. We're building Hedra Studio, a multimodal creation platform capable of control, emotion, and creative intelligence. At the core of Hedra Studio is our Character-3 foundation model, the first omnimodal model in production. Character-3 jointly reasons across image, text, and audio for more intelligent video generation - it's the next evolution of AI-driven content creation. At Hedra, we're a team of hard-working, passionate individuals seeking to fundamentally change content creation and build a generational company together. We value startup energy, initiative, and the ability to turn bold ideas into real products. Our team is fully in-person in SF/NY with a shared love for whiteboard problem-solving. Overview We are seeking a highly motivated Research Scientist to push the limits of long-form video generation, with a focus on auto-regressive modeling, causal attention mechanisms, and efficient sequence handling. The ideal candidate will have a deep understanding of temporal modeling in generative AI and experience building scalable architectures for multi-minute coherent video outputs. Responsibilities Design and implement long video generation architectures, with emphasis on auto-regressive generation, causal attention, and memory-efficient transformer designs. Develop methods for maintaining temporal and semantic coherence over long time horizons. Work closely with engineering to integrate research into production-grade pipelines. Stay on top of recent advances in long-context transformers, sequence compression, and scalable video generation. Present results internally and externally, including possible top-tier conference submissions. Qualifications PhD or strong research/industry experience in Computer Science, Machine Learning, or related fields, with a focus on sequence modeling or generative models. Deep understanding of transformer architectures, attention mechanisms, and auto-regressive modeling. Experience with long-context processing and memory-efficient computation. Proficiency in Python and PyTorch; ability to rapidly prototype and iterate on new architectures. A record of impactful research or large-scale system deployments. Benefits Competitive compensation + equity 401k (no match) Healthcare (Silver PPO Medical, Vision, Dental) Lunch and snacks at the office We encourage you to apply even if you don't meet every requirement - we value curiosity, creativity, and the drive to solve hard problems. #J-18808-Ljbffr

A pioneering AI security company located in San Francisco is seeking a Research Scientist to develop and enhance cutting-edge agent and machine learning security techniques. The ideal candidate will have expertise in Python and various LLM libraries, with a passion for innovation in a fast-paced startup environment. This role offers a competitive salary and the opportunity to work on groundbreaking AI solutions. #J-18808-Ljbffr

This is a job that we are recruiting for on behalf of one of our customers. To apply, speak to Jack. He's an AI agent that sends you unmissable jobs and then helps you ace the interview. He'll make sure you are considered for this role, and help you find others if you ask. Behavioral Research Scientist Salary: $140,000-$160,000 + Equity Company Description: VC-backed AI simulation platform Job Description: Shape the cognitive and behavioral foundations of AI agents for a cutting‑edge simulation engine. This role involves applying scientific depth to model decision‑making, attention, and heuristics, impacting how next‑generation digital products are designed. Join a team at the intersection of AI, behavioral science, and product experimentation, bringing real‑world impact to scalable systems. Location: San Francisco, USA Why this role is remarkable: Join a team creating category‑defining technology, building the simulation layer for adaptive software. Backed by top‑tier VCs and product/engineering leaders from leading tech companies. Apply deep behavioral science and cutting‑edge AI to solve complex product challenges with immediate impact. What you will do: Ground AI agents in validated behavioral and cognitive frameworks, modeling human decision‑making. Translate behavioral theories into practical agent architectures, defining user clusters and personas. Design and analyze in silico experiments to test agent responses and benchmark simulation realism. The ideal candidate: PhD or postdoc in Cognitive Science, Behavioral Economics, Psychology, or HCI. Proven experience conducting original research on decision‑making or behavioral modeling in digital contexts. Passionate about applying rigorous scientific research to real‑world, impactful AI systems. How to Apply: To apply for this job speak to Jack, our AI recruiter. Step 1. Visit our website Step 2. Click 'Speak with Jack'. Step 3. Login with your LinkedIn profile. Step 4. Talk to Jack for 20 minutes so he can understand your experience and ambitions Step 5. If the hiring manager would like to meet you, Jack will make the introduction #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

About P-1 AI: We are building an engineering AGI. We founded P-1 AI with the conviction that the greatest impact of artificial intelligence will be on the built world-helping mankind conquer nature and bend it to our will. Our first product is Archie, an AI engineer capable of quantitative and spatial reasoning over physical product domains that performs at the level of an entry‑level design engineer. We aim to put an Archie on every engineering team at every industrial company on earth. Our founding team includes the top minds in deep learning, model‑based engineering, and industries that are our customers. We just closed a $23 million seed round led by Radical Ventures that includes a number of other AI and industrial luminaries (from OpenAI, DeepMind, etc.). About the Role: We're seeking an exceptional AI Research Scientist to help us push the boundaries of AI applied to the physical world. This role blends cutting‑edge AI research with hands‑on engineering, and is ideal for someone who thrives at the intersection of ideas and implementation. You'll be leading projects that develop agentic AI systems designed to solve real‑world mechanical, electrical, and aerospace engineering problems-systems that think, remember, act, and adapt. This is not a “pure research” position: we're looking for a hacker‑scientist hybrid-someone who's published in top venues but is not afraid of any layer in the tech stack. What You'll Do: Design and implement agentic systems that autonomously solve physical engineering tasks. Develop advanced memory, retrieval, and planning architectures for LLM‑based agents. Apply (or invent) reinforcement learning strategies for reasoning, planning, and online adaptation. Contribute to both research strategy and technical implementation-this is a hands‑on role. Collaborate with a small, elite team of researchers and engineers across domains. Stay on the edge of what's possible and bring promising ideas into reality. About you: Have experience at the frontier of AI research (e.g., LLMs, RL, memory systems, agent architectures). Are passionate about applied problems-especially in mechanical, aerospace, or electrical engineering domains. Are fluent in Python and major ML/AI frameworks (PyTorch, JAX, etc.). Thrive in fast‑moving environments and feel comfortable working towards underspecified goals. Have a “whatever it takes” mindset: you're the kind of person makes things work. Can go from whiteboard to working prototype without waiting for someone else to “engineer” it. Preferred Qualifications: PhD in Computer Science, Robotics, Engineering, Math, or a related technical field (or equivalent experience). Relevant publications in top‑tier venues of your field. Experience with physical engineering domains a plus. Familiarity with agent tool‑use, retrieval‑augmented generation, or long‑term memory systems. Deep knowledge of reinforcement learning algorithms and practical challenges. Interview process: Initial screening - Head of Talent (30 mins) Hiring manager interview - Head of AI (45 mins) Technical Interview - AI Chief Scientist (45 mins) Culture fit / Q&A (maybe in person) - with co‑founder & CEO (45 mins) #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. Role overview We are seeking an exceptional Research Scientist to join our team, focusing on alignment and post-training techniques for large-scale video generation models. In this role, you will be at the forefront of ensuring our diffusion-based video models reliably produce high-quality, physically accurate and safe outputs that match human preferences and values. Responsibilities Lead research initiatives in alignment and post-training methods for video generation models, focusing on improved quality, reliability, and adherence to human intent Design and implement supervised fine-tuning and reinforcement learning from human feedback (RLHF) pipelines for video generation models Develop robust evaluation frameworks to measure model alignment, safety, and output quality Create and optimize data collection pipelines for human feedback and preferences Design and conduct experiments to validate alignment techniques and their scaling properties Collaborate with cross-functional teams to integrate alignment improvements into our production pipeline Stay at the cutting edge of the field by regularly reviewing academic literature in both generative AI and alignment Mentor junior researchers and foster a culture of responsible AI development Work closely with product teams to ensure alignment methods enhance rather than inhibit model capabilities 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., NeurIPS, ICML, ICLR) with a focus on reinforcement learning, alignment, or generative models Extensive experience implementing and optimizing large-scale training pipelines using PyTorch Deep understanding of reinforcement learning techniques, particularly RLHF Experience with distributed training systems and large-scale experiments Proven track record in designing and implementing robust evaluation frameworks Excellent communication skills with the ability to explain complex technical concepts to diverse audiences Strong software engineering skills and experience with complex shared codebases Ideal candidate will have: Experience with diffusion models or other generative architectures Background in fine-tuning large language models or generative models Experience working with human feedback data collection and annotation pipelines Strong aesthetic sense and understanding of video quality assessment Familiarity with alignment techniques such as constitutional AI or debate Track record of successful collaboration with product teams Experience with perceptual quality metrics and human evaluation design Contributions to open-source projects in AI alignment or generative AI Additional Information 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

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

A pioneering AI technology company in San Francisco seeks a Foundational AI Research Scientist (Speech) to advance speech understanding and generation. The role involves leading research in STT, TTS, and speech-to-speech modeling, requiring a Ph.D. and substantial experience in training foundational models. Candidates should possess deep expertise in modern sequence modeling architectures and a history of impactful research contributions. The company offers flexible paid time off and comprehensive health coverage. #J-18808-Ljbffr

Fund & Co-Investment Research Associate About Allocate Allocate is transforming private market investing by enabling wealth advisory firms to seamlessly build and manage high-quality private market programs. About the Role We're seeking a Fund & Co-Investment Research Associate to join our Private Investments team. This isn't a traditional allocator role, as you'll be a critical connector between world-class fund managers, wealth advisory CIOs, and help build and manage our technology platform. You'll evaluate venture capital and private equity opportunities, conduct manager diligence, and spend significant time with wealth advisor investment teams discussing curated deals. You need to deeply understand opportunities, answer sophisticated questions, and provide clear, accurate analysis that helps clients make confident investment decisions. Equally important, you'll own the completeness and accuracy of our platform content, ensuring all investment materials, copy, and compliance documentation stay current. Key Responsibilities Investment Research & Diligence: Conduct quantitative and qualitative research on private market managers and co-investment opportunities across venture capital, private equity, and adjacent asset classes. Prepare balanced investment analysis and recommendations. Client Engagement: Spend substantial time with wealth advisor CIOs and their investment teams discussing curated opportunities. Field detailed questions, articulate investment theses, and provide real-time analysis that demonstrates deep command of each deal. GP Relationship Development: Build and maintain relationships with fund managers, including structuring conversations, access discussions, and ongoing partnership development. Platform Completeness: Own platform content integrity-ensure investment materials are updated, copy is accurate and compliant, and all client-facing documentation metour quality standards. Sourcing & Pipeline Development: Proactively source differentiated fund and co-investment opportunities through targeted outreach, industry relationships, and market intelligence. Cross-Functional Collaboration: Partner with product, technology, and operations teams to refine platform capabilities and enhance the client investment experience. Portfolio Monitoring: Support post-investment updates, quarterly reporting, and ongoing portfolio analytics for client transparency. Market Intelligence: Develop insights and content that position Allocate as a leading voice in private markets. Qualifications Experience & Knowledge: 3+ years of experience in venture capital, private equity, wealth management, investment banking, or related fields. Deep industry knowledge of the VC/PE ecosystem, fund structures, and how institutional platforms operate. Strong understanding of private markets and alternative investments. Skills & Attributes: Hustler mentality: Proactive, resourceful, and self-directed-you don't wait to be told what to do. Exceptional communication: You can explain complex investment concepts clearly and handle sophisticated Q&A with institutional allocators. Highly personable: You build authentic relationships with both GPs and wealth advisory teams. Commercial mindset: You think about client needs, platform scalability, and growth. Startup DNA: You thrive in fast-paced environments, embrace ambiguity, and move quickly. Meticulous attention to detail: You ensure accuracy and compliance across all materials. Analytical excellence: You combine quantitative rigor with qualitative judgment. Not a Fit If You're: A pure allocator looking for a traditional fund-of-funds seat. More comfortable with analysis only role than relationship-building and client engagement. Seeking a slow-paced, process-heavy environment. Unfamiliar with how technology platforms operate. Why Allocate? Shape the infrastructure layer for an entire industry. Ability to immediately work with top VCs and PE firms, along with CIOs in the wealth advisory world. Allocate is one of the fastest-growing platforms in private markets. Palo Alto office in the heart of the venture ecosystem. High impact, high visibility work with real ownership and autonomy. Additional Information Location: Palo Alto, CA. Must be able to work in-office 4 days a week. Compensation: $160K-$200K base + bonus + stock equity. Benefits: Medical, dental, vision, 401(k), responsible time off. Employment: Full-time. Compliance: This role is subject to Allocate's Code of Ethics and all related compliance obligations. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire. Must have legal authorization to work in the U.S. now and in the future without visa sponsorship. #J-18808-Ljbffr