Research Scientist - LLM

Join Veracyte, a leader in transforming cancer care through innovative diagnostics that empower patients and clinicians alike. At Veracyte, we provide an inspiring work environment where you can make a significant impact on patients' lives while advancing your career. Our culture, known as the Veracyte way, emphasizes collaboration, resilience, and a commitment to excellence.Our Core Values:We Seek A Better Way: We boldly innovate and learn from challenges to improve cancer care.We Make It Happen: We prioritize urgency, quality, and enjoyment in our work.We Are Stronger Together: We foster open collaboration and celebrate our collective successes.We Care Deeply: We honor our diverse backgrounds and support each other in doing what is right.The Role:We are on the lookout for an enthusiastic Bioinformatics Research Scientist to join our Translational Bioinformatics group within the Bioinformatics and Data Science Team. This pivotal role involves leveraging computational and statistical techniques on extensive transcriptomic and genomic datasets, particularly focusing on prostate cancer biology and its clinical implications. The ideal candidate will play a key role in identifying clinically relevant molecular signatures that enhance disease stratification, prognosis, and the development of diagnostics, while effectively communicating findings to both scientific and clinical audiences. This position offers a unique opportunity to bridge the realms of data science, biology, and clinical research through close collaboration with scientists, clinicians, and cross-functional teams to convert complex data into actionable insights.

Join OpenAI as a Research Scientist and explore cutting-edge machine learning innovations. In this role, you will be at the forefront of developing groundbreaking techniques while advancing our team's research initiatives. Collaborate with talented peers across various teams to discover transformative ideas that scale effectively. We seek individuals who are passionate about pushing the boundaries of AI and want to contribute to our unified research vision.

Merge Labs is an innovative research facility dedicated to merging biological sciences and artificial intelligence to enhance human capability, autonomy, and experience. Our mission is to pioneer revolutionary methodologies in brain-computer interfaces that facilitate high-bandwidth interactions with the brain, seamlessly integrate advanced AI, and maintain safety and accessibility for all users.About the TeamAt Merge, we are addressing some of the most ambitious challenges in molecular engineering, synthetic biology, and neuroscience. Our Research Platform Team is responsible for creating the experimental frameworks necessary to tackle these challenges with exceptional speed and precision. The tools and methodologies developed by our team significantly enhance molecular assembly, protein expression, mammalian cell culture, advanced microscopy, sequencing, and unique custom techniques. We collaborate with program teams to establish and optimize these capabilities, implement automation where beneficial, and integrate with our data science and machine learning pipelines, continuously pushing the boundaries of throughput and innovation.About the RoleAs a Platform Scientist, you will be instrumental in developing high-efficiency and high-throughput experimental pipelines that accelerate research initiatives. You will work closely with program leads, project scientists, data scientists, and engineers, leading your work and potentially recruiting additional team members as necessary.Key Responsibilities:Collaborate with program leads and scientists to identify critical experimental requirements and workflows.Develop processes to facilitate high-throughput and/or high-efficiency experiments, including reagent production and analysis.Scope, procure, construct, program, and validate instruments to support experimental workflows.Ensure the quality, reliability, and integrity of data generated from automated pipelines, including defining and implementing suitable quality control checkpoints.Work alongside data science and machine learning engineers to incorporate metadata tracking, computational design, and analysis into experimental pipelines.Partner with electrical, mechanical, and software engineers to create custom setups.Innovate and validate concepts to enhance experimental throughput.

OverviewBecome an integral part of our dynamic R&D team dedicated to developing fully automated research systems that push the boundaries of AI. Zochi has achieved a milestone by publishing the first entirely AI-generated A* conference paper. Locus has set a new industry standard as the first AI system to surpass human experts in AI R&D.Key ResponsibilitiesConceptualize and develop innovative architectures for automated research.Work collaboratively within a specialized team of researchers addressing cutting-edge challenges in long-horizon agentic capabilities, post-training for open-ended objectives, and environment crafting.Document and publish key internal findings alongside success stories from external collaborations.QualificationsPhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline. Outstanding candidates with significant research contributions are encouraged to apply, regardless of formal qualifications.Demonstrated history of impactful AI/ML research contributions in academic or corporate environments.Expertise in developing long-horizon, multi-agent systems and/or model post-training, especially in scientific domains or for open-ended discovery objectives.A strong passion for advancing problem-solving processes and scientific discovery, thriving in high-autonomy roles and environments.Our CultureCompetitive compensation and equity options.Unlimited Paid Time Off (PTO), emphasizing team collaboration and a community-focused workplace.Opportunities for conference participation and engagement in community initiatives.Empowered roles with high levels of responsibility.#1: We are a small, passionate team of leading investors, researchers, and industry experts committed to the mission of accelerating discovery. Join us.

About the TeamJoin the innovative Post-Training team at OpenAI, where we focus on refining and elevating pre-trained models for deployment in ChatGPT, our API, and future products. Collaborating closely with various research and product teams, we conduct crucial research that prepares our models for real-world deployment to millions of users, ensuring they are safe, efficient, and reliable.About the RoleAs a Research Engineer / Scientist, you will spearhead the research and development of enhancements to our models. Our work intersects reinforcement learning and product development, aiming to create cutting-edge solutions.We seek passionate individuals with robust machine learning engineering skills and research experience, particularly with innovative and powerful models. The ideal candidate will be driven by a commitment to product-oriented research.This position is located in San Francisco, CA, and follows a hybrid work model requiring three days in the office each week. Relocation assistance is available for new employees.In this role, you will:Lead and execute a research agenda aimed at enhancing model capabilities and performance.Work collaboratively with research and product teams to empower customers to optimize their models.Develop robust evaluation frameworks to monitor and assess modeling advancements.Design, implement, test, and debug code across our research stack.You may excel in this role if you:Possess a deep understanding of machine learning and its applications.Have experience with relevant models and methodologies for evaluating model improvements.Are adept at navigating large ML codebases for debugging purposes.Thrive in a fast-paced and technically intricate environment.About OpenAIOpenAI is a pioneering AI research and deployment organization dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We are committed to pushing the boundaries of AI capabilities while prioritizing safety and human-centric values in our products. Our mission is to embrace diverse perspectives, voices, and experiences that represent the full spectrum of humanity, as we strive for a future where AI is a powerful ally for everyone.

About Our TeamJoin the forefront of AI innovation with the RL and Reasoning team at OpenAI. Our team is dedicated to advancing reinforcement learning research and has pioneered transformative projects, including o1 and o3. We are committed to pushing the limits of generative models while ensuring their scalable deployment.About the RoleAs a Research Engineer/Research Scientist at OpenAI, you will play a pivotal role in enhancing AI alignment and capabilities through state-of-the-art reinforcement learning techniques. Your contributions will be essential in training intelligent, aligned, and versatile agents that power various AI models.We seek individuals with a solid foundation in reinforcement learning research, agile coding skills, and a passion for rapid iteration.This position is located in San Francisco, CA, and follows a hybrid work model of three days in the office per week. We also provide relocation assistance for new hires.You may excel in this role if:You are enthusiastic about being at the cutting edge of RL and language model research.You take initiative, owning ideas and driving them to fruition.You value principled methodologies, conducting simple experiments in controlled environments to draw trustworthy conclusions.You thrive in a fast-paced, complex technical environment where rapid iteration is essential.You are adept at navigating extensive ML codebases to troubleshoot and enhance them.You possess a profound understanding of machine learning and its applications.About OpenAIOpenAI is a pioneering AI research and deployment organization committed to ensuring that general-purpose artificial intelligence serves the greater good for humanity. We strive to push the boundaries of AI system capabilities while prioritizing safe deployment through our innovative products. We recognize AI as a powerful tool that must be developed with safety and human-centric principles, embracing diverse perspectives to reflect the full spectrum of humanity.We are proud to be an equal opportunity employer, welcoming applicants from all backgrounds without discrimination based on race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or any other legally protected characteristic.

Join the Prima Mente TeamAt Prima Mente, we are at the forefront of biology and artificial intelligence. Our innovative lab is dedicated to generating unique data, creating versatile biological foundation models, and translating groundbreaking discoveries into both research and clinical applications. Our primary focus is on unraveling the complexities of the brain to enhance its health, safeguard it against neurological disorders, and foster cognitive enhancement. Our diverse team of AI researchers, experimentalists, clinicians, and operations experts spans across London, San Francisco, and Dubai.Position Overview - Multi-omicsIn this role, you will be instrumental in formulating and questioning significant biological hypotheses aimed at discovering biomarkers and targets pertinent to neurological diseases.Key Responsibilities:Conduct feature engineering and prepare datasets for machine learning applications and foundational AI model training.Analyze in-house wet lab experiments to develop proprietary methods and generate data for our models.Build and optimize multi-omic bioinformatics pipelines.Establish and manage collaborative research initiatives with academic and industry partners focused on Alzheimer's disease biology.Growth ExpectationsWithin 1 month: You will independently manage your own analyses and experiments using our cloud computing environment, creating bespoke workflows to efficiently process data.Within 3 months: Your research will be seamlessly integrated into our AI models.Within 6 months: Your pipelines will be running in automated production, contributing to daily AI model training. You will collaborate closely with AI/ML engineers and lab scientists, leading the technical aspects of external partnerships.Who You AreYou aspire to push the boundaries of what is achievable at the intersection of AI and biology. You possess experience in deriving novel biological insights from multi-omic, multi-modal datasets, along with a track record of top-tier publications and/or patents.We understand that not every candidate will meet every qualification. We encourage strong applicants to apply, even if they specialize in certain areas and wish to expand their expertise in others.Preferred Qualifications:Practical experience in generating insights from biological datasets (genomics, epigenetics, transcriptomics, proteomics, ATAC-Seq).Proficient software engineering skills, including the ability to write high-quality code for operational purposes.

About Prima MentePrima Mente is a pioneering AI lab specializing in frontier biology. We are committed to developing our own data, constructing versatile biological foundation models, and translating groundbreaking discoveries into tangible research and clinical results. Our primary objective is to advance our understanding of the brain, aiming to protect it from neurological diseases while enhancing its health. Our talented team of AI researchers, experimentalists, clinicians, and operators is strategically located in London, San Francisco, and Dubai.Role Overview:As our inaugural Forward Deployed Scientist, you will integrate our flagship model, Pleiades, with early partners to explore potential research outcomes and product hypotheses, while leading the development of our Forward Deployment Strategy.Key Responsibilities:Design, manage, and oversee the Forward Deployment function.Directly handle the customer implementation strategy and execution from start to finish.Collaborate closely with early design partners, including research institutes and healthcare providers, to gain a comprehensive understanding of their needs regarding cfDNA fragment analysis, epigenetic embedding, multi-omic integration, and diagnostic reporting.Transform real-world challenges into actionable, deployable solutions by designing and constructing custom pipelines, data ingestion processes, model integration, and tailored output handling.Serve as the primary technical liaison, building trust and guiding the customer's teams.Establish deployment best practices and identify reusable patterns for future implementations.Incorporate findings from deployments back into the R&D roadmap, aiding in prioritizing model enhancements and new features.Who You Are:We value diverse skill sets and do not expect candidates to meet every qualification. Strong candidates typically possess depth in some areas while showing interest in others.Exceptional customer engagement and empathy: you can effectively communicate complex systems to non-technical stakeholders and understand their business challenges, translating these into technical specifications.Strong technical proficiency: adept in programming and scripting languages, particularly Python, with the ability to build bioinformatics pipelines and refine ML models for production settings.Experience in creating tools or frameworks for ML/AI workloads, including data pipelines, infrastructure, and CI/CD processes.A proactive approach towards rapid iteration and adapting project scopes as needed.

Join Our Team as a Research ScientistAt Parallel, we are at the forefront of web infrastructure innovation, enabling businesses across sectors such as sales, marketing, insurance, and technology to harness the power of AI. Our state-of-the-art products empower users to develop superior AI agents with seamless and flexible access to the web.With significant backing of $130 million from prominent investors like Kleiner Perkins, Index Ventures, and Spark Capital, we are dedicated to redefining the web for artificial intelligence. As we expand, we're assembling a top-tier team of engineers, designers, marketers, sales experts, researchers, and operational specialists committed to our vision.Your Role: As a Research Scientist, you will tackle the challenge of training and scaling models designed to enhance web indexing capabilities.About You: You possess a profound understanding of contemporary models and training methodologies. You enjoy engaging in discussions about the convergence of search, recommendations, and transformer models, and are passionate about translating your research into impactful products and systems utilized by millions.

Join Mithrl as a Lead Bioinformatics EngineerAt Mithrl, we envision a future where groundbreaking medicines are swiftly delivered to patients, transforming the landscape of health care.Mithrl is pioneering the world's first commercially available AI Co-Scientist, a revolutionary discovery engine that converts complex biological data into actionable insights in mere minutes. By simply asking questions in natural language, scientists receive immediate responses with comprehensive analyses, innovative targets, hypotheses, and patent-ready reports.Our impressive growth trajectory includes:12X year-over-year revenue growthTrusted by top-tier biotech firms and major pharmaceutical companies across three continentsFacilitating real breakthroughs from target discovery to patient outcomes.About the RoleWe are in search of an innovative Lead Bioinformatics Pipeline Engineer to architect and expand Mithrl’s multimodal scientific processing pipelines. You will be responsible for developing workflows that convert raw biological data into clean, reproducible outputs that fuel Mithrl’s AI Co-Scientist. Your work will encompass a range of modalities including microarray, imaging, spatial transcriptomics, genomics, epigenomics, flow cytometry, and more.This pivotal role lies at the core of our technical infrastructure. You will design Nextflow and nf-core style pipelines, implement modality-specific validation and quality control layers, and collaborate closely with our Tabular Data Team and Knowledge Curation Team to ensure seamless data harmonization, variable ID mapping, and schema alignment. Your contributions will enable scientists to pose inquiries and receive accurate, data-driven answers instantaneously.If you are passionate about constructing robust scientific workflows and tackling high-impact challenges, you will find your place here.

Zyphra is a pioneering artificial intelligence firm located in the vibrant city of San Francisco, California.About the Role:We are seeking a passionate Research Scientist to join our dynamic Agency and Reasoning Team at Zyphra. In this role, you will conduct cutting-edge research in reinforcement learning, post-training methodologies, and human preference learning. Your innovative ideas will be instrumental in shaping our next-generation language models, enabling their application on a large scale.What We Desire:A strong sense of research intuition and tasteCapability to navigate a research project from initial concept to execution and documentationProficiency in implementation and prototypingA quick thinker who can rapidly transform ideas into experimental frameworksAbility to collaborate effectively in a fast-paced research environmentAn insatiable curiosity and enthusiasm for the study of intelligence.Qualifications:Proven experience and skill in reinforcement learning, particularly in the context of language model reasoning or classical RL tasksFamiliarity with language-model-supervised fine-tuning and preference-learning techniques, such as DPO and simPO.Experience with methods for context-length extensionStrong intuitive understanding of model behaviors, with the ability to refine them through iterative fine-tuningInterest in engaging deeply with data and dedicating time to data engineering and synthetic data generationA postgraduate degree in a scientific discipline (Computer Science, Electrical Engineering, Mathematics, Physics)Published research in reputable machine learning venuesExpertise in PyTorch and PythonEagerness and aptitude for rapidly acquiring new knowledge and implementing innovative conceptsExceptional communication and teamwork abilities, capable of contributing to both research and large-scale engineering effortsWhy Join Zyphra?We champion creative and unconventional ideas and are prepared to invest significantly in innovative concepts.Our culture fosters collaboration, curiosity, and intellectual growth.

Zyphra is a cutting-edge artificial intelligence firm headquartered in the vibrant city of San Francisco, California.Position Overview:As a Research Scientist specializing in Model Architectures, you will play a pivotal role in Zyphra’s AI Architecture Research Team. Your responsibilities will include the design and thorough evaluation of innovative model architectures and training methodologies aimed at enhancing essential modeling capabilities (e.g., loss per flop or loss per parameter) and tackling core limitations inherent in current models. You will collaborate closely with our pre-training team to ensure that your findings are seamlessly integrated into our next-generation models.Qualifications:A strong research acumen and intuition.Proven ability to navigate research projects from initial conception to execution and final write-up.Exceptional implementation and prototyping skills, with the capability to swiftly transform ideas into experimental outcomes.A collaborative spirit and the ability to thrive in a fast-paced research environment.A deep curiosity and enthusiasm for understanding intelligence.Requirements:Experience with long-term memory, RAG/retrieval systems, dynamic/adaptive computation, and alternative credit assignment strategies.Knowledge of reinforcement learning, control theory, and signal processing techniques.A passion for exploring and critically evaluating unconventional ideas, with the ability to maintain a unique perspective.Familiarity with modern training pipelines and the hardware necessities for designing efficient architectures compatible with GPU hardware.Strong understanding of experimental methodologies for conducting rigorous ablations and hypothesis testing.High proficiency in PyTorch and Python programming.Ability to quickly assimilate into large pre-existing codebases and contribute effectively.Prior publication of machine learning research in reputable venues.Postgraduate degree in a scientific discipline (e.g., Computer Science, Electrical Engineering, Mathematics, Physics).Why Join Zyphra?We emphasize a structured research methodology that systematically addresses ambitious challenges in AI.

About AfterQuery AfterQuery partners with leading AI labs to advance training data and evaluation frameworks. The team builds high-signal datasets and runs thorough evaluations that go beyond standard benchmarks. As a post-Series A, early-stage company in San Francisco, AfterQuery gives each team member room to shape the future of AI models. Role Overview: Research Scientist - Frontier Data This role focuses on designing datasets and developing evaluation systems that influence how top AI models are trained and assessed. Working closely with research teams at major AI labs, the scientist explores new data collection techniques, investigates where models fall short, and sets up metrics to track progress. The work is hands-on and experimental, moving quickly from hypothesis to live testing and directly impacting large-scale model training. Key Responsibilities Design data slides and analyze data structures to uncover model weaknesses in areas like finance, software development, and enterprise operations. Build and refine evaluation rubrics and reward signals for RLHF and RLVR training approaches. Study annotator behavior and run experiments to improve model capabilities across different domains. Develop quantitative frameworks to measure dataset quality, diversity, and their effect on model alignment and performance. Work with research teams to turn training objectives into concrete data and evaluation needs. What We Look For Experience as an undergraduate or master’s research student (PhD not required). Background or internships with RL environments or AI safety and benchmarking organizations (e.g., METR, Artificial Analysis) is a strong plus. Genuine interest in how data structure, selection, and quality affect model outcomes. Demonstrated skill in designing experiments, acting quickly, and extracting insights from complex data. Comfort working across sectors such as finance, software engineering, and policy. Strong quantitative background and familiarity with LLM training pipelines, RLHF/RLVR methods, or evaluation frameworks. A hands-on mindset focused on building practical solutions.

About Our TeamJoin the Foundations Research team, where we tackle ambitious and innovative projects that could redefine the future of AI. Our mission is to enhance the science behind our training and scaling initiatives, focusing on pioneering frontier models. We are dedicated to advancing data utilization, scaling methodologies, optimization strategies, model architectures, and efficiency enhancements to accelerate our scientific breakthroughs.About the PositionWe are on the lookout for a dynamic technical research lead to spearhead our embeddings-focused retrieval initiatives. You will oversee a talented team of research scientists and engineers committed to developing foundational technologies that enable models to access and utilize the right information precisely when needed. This includes crafting innovative embedding training objectives, architecting scalable vector storage, and implementing adaptive indexing techniques.This pivotal role will contribute to various OpenAI products and internal research initiatives, offering opportunities for scientific publication and significant technical influence.This position is located in San Francisco, CA, where we embrace a hybrid work model, requiring three days in the office weekly, and we provide relocation assistance for new hires.Your ResponsibilitiesLead cutting-edge research on embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning.Supervise a team of researchers and engineers in building an end-to-end infrastructure for training, evaluating, and integrating embeddings into advanced models.Drive advancements in dense, sparse, and hybrid representation techniques, metric learning, and retrieval systems.Work collaboratively with Pretraining, Inference, and other Research teams to seamlessly integrate retrieval throughout the model lifecycle.Contribute to OpenAI's ambitious vision of developing AI systems with robust memory and knowledge access capabilities rooted in learned representations.You Will Excel in This Role If You PossessA proven track record of leading high-performance teams of researchers or engineers within ML infrastructure or foundational research.In-depth technical knowledge in representation learning, embedding models, or vector retrieval systems.Familiarity with transformer-based large language models and their interaction with embedding spaces and objectives.Research experience in areas such as contrastive learning and retrieval-augmented generation.

Join the Center for AI Safety (CAIS), a pioneering research and advocacy organization dedicated to addressing the societal-scale risks posed by artificial intelligence. We tackle the most pressing challenges in AI through rigorous technical research, innovative field-building initiatives, and proactive policy engagement, in collaboration with our sister organization, the Center for AI Safety Action Fund.As a Research Scientist, you will spearhead and conduct transformative research aimed at enhancing the safety and dependability of cutting-edge AI systems. Your responsibilities will include designing and executing experiments on large language models, developing the necessary tools for training and evaluating models at scale, and converting your findings into publishable research. You will work closely with CAIS researchers and external partners from academia and industry, utilizing our compute cluster for large-scale model training and evaluation. Your research will focus on critical areas such as AI honesty, robustness, transparency, and the detection of trojan/backdoor behaviors, all aimed at mitigating real-world risks associated with advanced AI technologies.

AI Research ScientistAt Substrate, we are tackling a critical technological challenge that impacts the United States. Positioned at the crossroads of advanced manufacturing and innovative physics, our mission is to develop transformative technologies that will revolutionize the semiconductor industry and bolster America's technological dominance. Our team comprises top-tier scientists, engineers, and technical specialists dedicated to pushing the boundaries of technology for the benefit of the nation.As an AI Research Scientist, you will play a key role in enhancing and accelerating research and development processes by harnessing machine learning techniques for scientific simulations and modeling. You will also focus on establishing internal AI capabilities throughout our organization. This position merges cutting-edge physics with artificial intelligence, requiring hands-on development of AI-enhanced tools that facilitate groundbreaking research. You will also contribute to building the infrastructure and expertise required for our technical teams to effectively use AI in their workflows. Whether you are a physicist who has adopted machine learning or an AI expert with a solid scientific background, you will be instrumental in shaping our approach to utilizing AI to expedite our internal R&D efforts.

Join Scale Labs as a Research Scientist — Agent RobustnessScale is the premier partner for data and evaluation within the forefront of AI innovation, playing a crucial role in understanding and safeguarding AI models and systems. Building on our extensive expertise, Scale Labs has initiated a dedicated team focused on policy research, aiming to connect AI research with global policymakers to facilitate informed, scientifically grounded decisions regarding AI risks and capabilities.Our research addresses complex challenges in agent robustness, AI control protocols, and AI risk evaluations, empowering governments, industries, and the public to comprehend and mitigate AI risks while promoting AI adoption. This team collaborates across various sectors, including industry, public services, and academia, and regularly disseminates our findings. We are actively inviting skilled researchers to contribute to this vision.As a Research Scientist specializing in Agent Robustness, you will tackle foundational challenges in creating AI agents that are both safe and aligned with human values. Your responsibilities may include:Investigating the science behind AI agent capabilities, focusing on safety, risk factors, and benchmarking methodologies.Designing and building testing harnesses to evaluate AI agents' tendencies to engage in harmful actions under user pressure or environmental manipulation.Creating exploits and mitigations for new failure modes that emerge as AI agents gain capabilities such as coding, web browsing, and computer usage.Characterizing and developing mitigations for potential failure modes or broader risks involving multiple interacting AI agents.

About the RoleAs a Research Scientist focused on Pretraining, you will develop the foundational intelligence layer for robotics. Our mission involves training expansive robot foundation models utilizing vast multimodal datasets that encompass video, proprioception, action traces, language, and beyond. You will lead and execute large-scale training initiatives that imbue our models with groundbreaking general capabilities applicable across various embodiments, tasks, and environments. Your work will involve deeply engaging with all facets of robotic data.Key Responsibilities:Design and conduct extensive pretraining efforts for robot foundation models, employing transformer and diffusion architectures.Establish model architectures, objectives, and training curricula that leverage multimodal robotic data, including vision, action, state, and language inputs.Create scalable data mixtures and sampling strategies to effectively utilize petabyte-scale datasets.Direct data collection operations and explore new avenues for dataset sourcing.Conduct ablation studies to uncover insights regarding scaling laws, data quality impacts, and architectural trade-offs.Collaborate closely with ML Infrastructure and Systems teams to enhance cluster utilization, throughput, and reliability.Transform raw robotic interaction data into versatile model capabilities.Ideal Candidate Profile:Extensive experience in training large transformer or diffusion models at scale, particularly in generative tasks such as language, audio, or video modeling.Proven leadership or significant contribution to multi-node, multi-GPU distributed training initiatives.Experience with scaling laws, optimization dynamics, and understanding large-model failure modes.Strong foundation in PyTorch and comfort in debugging across all layers of the computational stack.Appreciation for empirical rigor paired with rapid iteration speed.Enthusiasm for building general-purpose robot intelligence from foundational principles.About GeneralistAt Generalist, we are dedicated to realizing the potential of general-purpose robots. We envision a future where industries and households thrive through innovative collaborations between humans and machines. Our robots are designed to enhance productivity and facilitate the achievement of more ambitious goals.

About GranicaGranica is an innovative AI research and infrastructure firm dedicated to creating reliable, steerable representations of enterprise data.We establish trust through Crunch, a policy-driven health layer optimizing large tabular datasets for efficiency, reliability, and reversibility. Utilizing this foundation, we are developing Large Tabular Models—systems designed to learn cross-column and relational structures, delivering trustworthy answers and automation with integrated provenance and governance.Our MissionCurrent AI capabilities are hindered not only by model design but also by the inefficiencies of the data that supports it. At scale, each redundant byte, poorly organized dataset, and inefficient data pathway contributes to significant costs, latency, and energy waste.Granica’s mission is to eliminate these inefficiencies. We leverage groundbreaking research in information theory, probabilistic modeling, and distributed systems to craft self-optimizing data infrastructure: systems that continually enhance how information is represented and utilized by AI.Led by Prof. Andrea Montanari from Stanford, Granica’s Research group merges advances in information theory with learning efficiency in large-scale distributed systems. We collectively believe that the next significant leap in AI will originate from innovations in efficient systems, rather than merely larger models.Granica is at the forefront of developing a new category of structured AI models: foundational models designed to learn and reason from the relational, tabular, and structured data that drives the global economy. While many focus on unstructured text or media, we are venturing into the next frontier: systems capable of comprehending and reasoning over structured information.Your ContributionsCreate and prototype algorithms that form the core of structured AI, enhancing representation learning and efficient information modeling for enterprise and tabular data at petabyte scale.Develop adaptive learners merging statistical learning theory with systems optimization at scale, contributing to a new generation of foundational models for structured information.Design architectures that unify symbolic, relational, and neural components, enabling AI systems to reason directly over structured enterprise data.Construct cost models and optimization frameworks that enhance the efficiency of structured learning, both computationally and economically.