Research Engineer/Scientist at Preference Model | San Francisco

About UsAt Preference Model, we are pioneering the development of next-generation training data that drives the future of artificial intelligence. While current models demonstrate significant capabilities, they often fall short in diverse applications due to many tasks being out of distribution. We create reinforcement learning environments where models tackle real-world research and engineering challenges, continuously iterating and learning from authentic feedback loops.Our founding team, with experience from Anthropic’s data division, has built the infrastructure and datasets that support the Claude AI. We collaborate with top-tier AI laboratories to accelerate AI's journey toward its transformative potential, and we are proudly backed by a16z.About the RoleWe envision a future where models can autonomously train on their weaknesses. We seek innovative thinkers eager to explore the limits of self-directed learning. In this position, you will meld research with engineering, implementing cutting-edge methodologies and influencing research trajectories.Representative Projects:Architect and enhance our core reinforcement learning infrastructure, developing clean training abstractions and distributed experiment management systems to accommodate increasingly complex research workflows.Design, implement, and validate training environments, evaluations, and methodologies for reinforcement learning agents.Enhance performance through profiling, optimization, and benchmarking. Implement efficient caching techniques and debug distributed systems to expedite training and evaluation processes.Collaborate with cross-functional teams in research and engineering to establish automated testing frameworks, design user-friendly APIs, and build scalable infrastructure that propels AI research forward.You May Be a Good Fit If You:Are proficient in Python and familiar with frameworks like PyTorch or Jax.Have hands-on experience in training and conducting machine learning research on large language models.Can effectively balance research exploration with practical engineering implementation.Enjoy pair programming and prioritize code quality, testing, and performance.Possess strong systems design and communication skills.Have a solid understanding of reinforcement learning algorithms and stay updated with current publications in the field.

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 UsAt Preference Model, we are revolutionizing the future of AI by developing the next generation of training data. While current models demonstrate great power, their effectiveness is limited in diverse applications due to many tasks being out of distribution. We create reinforcement learning environments where models can face real-world research and engineering challenges, allowing them to iterate and learn via realistic feedback loops.Our founding team, hailing from Anthropic's data team, has a rich background in building data infrastructure, tokenizers, and datasets that power Claude. We collaborate with leading AI labs to accelerate AI’s transformative potential and are proudly backed by a16z.About the RoleWe are looking for skilled Machine Learning Engineers to join our efforts in constructing distributed training infrastructure for our reinforcement learning initiatives. Your responsibilities will include:Designing and implementing scalable distributed training infrastructure utilizing PyTorch and Ray.Developing automation tools for monitoring, debugging, and recovery in distributed training environments.Ensuring the reliability, security, and performance of infrastructure to meet the high demands of large-scale machine learning workloads.About YouWe seek individuals with the following qualifications and traits:Required Technical Skills:Experience in building and managing ML infrastructure at scale.Expertise in PyTorch and distributed training paradigms.Hands-on experience with Ray.Familiarity with at least one modern RL training framework such as verl, NeMo-RL, ART, Atropos, or similar.Proficiency in Python and systems programming.Experience with container orchestration tools (Kubernetes), and infrastructure as code methodologies (Terraform).What Makes You Successful:Strong systems thinking with an ability to design for scalability.Exceptional debugging skills across the entire technology stack.A collaborative mindset and strong communication skills to effectively liaise with researchers and engineers.Self-motivated and capable of solving problems independently while taking ownership of projects.

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.

About World Labs: At World Labs, we create foundational world models capable of perceiving, generating, reasoning, and interacting with the 3D environment. Our mission is to unlock the full potential of AI through spatial intelligence, transforming perception into action, reasoning into insight, and imagination into creation. We believe that spatial intelligence will revolutionize storytelling, creativity, design, simulation, and immersive experiences across both virtual and physical realms. Our world-class team is driven by curiosity and passion, boasting diverse backgrounds in technology, from AI research and systems engineering to product design. This synergy fosters a tight feedback loop between our cutting-edge research and user-empowering products. Role Overview We are seeking an innovative Research Scientist specializing in generative modeling, especially diffusion models, to join our modeling team. This position is ideal for individuals with extensive expertise in applying diffusion models to images, videos, or 3D assets and scenes. While not mandatory, experience in any of the following areas will be considered a significant advantage: Large-scale model trainingResearch in 3D computer vision In this role, you will work closely with researchers, engineers, and product teams to translate advanced 3D modeling and machine learning techniques into practical applications, ensuring our technology stays at the forefront of visual innovation. This position entails substantial hands-on research and engineering work, taking projects from conception to production deployment. Key Responsibilities Design, implement, and train large-scale diffusion models for generating 3D worlds. Develop and experiment with large-scale diffusion models to introduce novel control signals, align with target aesthetic preferences, or optimize for efficient inference. Collaborate closely with research and product teams to comprehend and translate product requirements into actionable technical roadmaps. Contribute actively to all phases of model development, including data curation, experimentation, evaluation, and deployment. Continuously investigate and integrate the latest research in diffusion and generative AI. Serve as a key technical resource within the team, mentoring peers and promoting best practices in generative modeling and machine learning engineering.

At Genmo, we are pioneering advancements in video generation technology through our state-of-the-art research lab. Our mission is to develop open models that contribute to the evolution of Artificial General Intelligence (AGI). Join us as we redefine the capabilities of AI and explore the vast potential of video generation.Role Overview:We are on the lookout for an outstanding Research Scientist specializing in diffusion models to be a part of our innovative team. Your primary focus will be on creating advanced diffusion models aimed at transforming text into captivating video content. This role places you at the cutting edge of AI research, where you will devise new architectures and algorithms to generate visually appealing and coherent videos from textual descriptions.

Preference Model creates new types of training data to help artificial intelligence systems improve beyond their current limits. The team specializes in building reinforcement learning environments that test both research and engineering abilities, giving models the chance to learn from realistic feedback. Founded by former members of Anthropic’s data division, Preference Model draws on experience building data infrastructure, tokenizers, and datasets for Claude. The company partners with top AI labs and is backed by a16z. Role overview This entry-level machine learning engineer position is based in San Francisco and is intended for recent graduates. The focus is on building and maintaining the infrastructure that powers Preference Model’s reinforcement learning training pipeline. The team is small, so each engineer takes responsibility for their projects. Deep production experience is not required, but strong technical fundamentals, curiosity about reinforcement learning, and the ability to learn quickly are essential. What you will do Develop and scale distributed training systems with PyTorch Design automation for monitoring, debugging, and recovery during large-scale training runs Collaborate with researchers to turn RL training experiments into dependable infrastructure Enhance performance and reliability for GPU and TPU workloads Requirements Recent graduate (BS, MS, or PhD) in Computer Science, Machine Learning, or a related field Interest in reinforcement learning and AI infrastructure

Genmo is a pioneering research laboratory dedicated to advancing cutting-edge models for video generation, with the mission of unlocking the creative potential of Artificial General Intelligence (AGI). We invite you to be a part of our innovative team, where you can contribute to shaping the future of AI and expanding the horizons of video generation technology.Role Overview:We are on the lookout for a talented Research Scientist to join our dynamic team, specializing in alignment and post-training methodologies for large-scale video generation models. In this pivotal role, you will be instrumental in ensuring our diffusion-based video models consistently deliver high-quality, physically accurate, and safe outputs that align with human values and preferences.Key Responsibilities:Lead groundbreaking research initiatives in alignment and post-training strategies for video generation models, prioritizing enhanced quality, reliability, and alignment with human intent.Design and implement supervised fine-tuning and reinforcement learning from human feedback (RLHF) pipelines for video generation models.Establish robust evaluation frameworks to assess model alignment, safety, and output quality.Create and optimize data collection pipelines for capturing human feedback and preferences.Conduct experiments to validate alignment techniques and their scalability.Collaborate with cross-functional teams to incorporate alignment enhancements into our production workflow.Stay abreast of the latest developments by reviewing academic literature in generative AI and alignment.Mentor junior researchers and promote a culture of responsible AI development.Partner closely with product teams to ensure that alignment methods enhance model capabilities.Qualifications:Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.Demonstrated excellence with a strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR) focusing on reinforcement learning, alignment, or generative models.Extensive experience in implementing and optimizing large-scale training pipelines utilizing PyTorch.In-depth understanding of reinforcement learning techniques, especially RLHF.Proficient in distributed training systems and conducting large-scale experiments.Proven ability to design and implement robust evaluation strategies for models.

RoleAs a Research Scientist at OpenEvidence, you will explore the potential of cutting-edge models, leveraging a strong research foundation to build practical systems rather than merely publishing papers. You will take ownership of projects from conception to execution, valuing evaluation and quantitative validation as integral components of your work.We seek exceptional innovators who are not confined to narrow specializations. Our engineers and scientists collaborate across diverse products and projects, driving impactful work wherever their skills can shine.About UsOpenEvidence is the leading medical AI platform globally, rapidly adopted by over 40% of US clinicians within just one year through organic, product-driven growth. With a valuation of $12B, our engineering team comprises 30 talented individuals from prestigious institutions like MIT, Harvard, and Stanford. We believe that transformative products emerge from a select group of exceptional builders who are empowered to take initiative and work swiftly toward focused goals. Join us as we embark on a unique opportunity to establish the standard platform for medical AI.CultureWe hold that work should engage at a world-class level. Building from 0 to 1 and scaling from 1 to 1000 is akin to a professional sport, where uncompromising excellence is the standard. We assert that the creation of unprecedented technologies requires complete ownership, and significant achievements arise when individuals commit to them.Who Are You?If your goal is to clock in and out with minimal engagement, this role is not for you. If you prefer to write papers rather than roll up your sleeves and get involved in creating impactful solutions that influence millions, this position may be your calling. The ideal candidate is a remarkable builder—intelligent, ambitious, resourceful, self-driven, meticulous, motivated, diligent, and humble. We recognize this profile is rare, which is why we have only identified 30 such individuals and are eager to find more.LocationAll engineering roles are in-person, requiring attendance five days a week in either San Francisco or Miami.

Join the Center for AI Safety (CAIS), a premier research and advocacy organization dedicated to addressing the complex societal challenges posed by artificial intelligence (AI). Our mission focuses on mitigating large-scale risks associated with AI through groundbreaking technical research, strategic initiatives, and proactive policy engagement, in collaboration with our sister organization, the Center for AI Safety Action Fund. As a Senior Research Scientist at CAIS, you will spearhead and execute transformative research aimed at enhancing the safety and reliability of advanced AI systems. You will take ownership of significant open challenges, driving them to successful publication. We seek individuals who set a high standard for research excellence and contribute innovative ideas to elevate our collective understanding. Your role will involve designing and conducting experiments on large language models, developing the necessary tools for large-scale model training and evaluation, and translating findings into publishable research. Close collaboration with CAIS researchers and external academic and industry partners will be essential, utilizing our compute cluster for extensive training and evaluation projects. Research areas include AI honesty, robustness, transparency, and mitigating trojan/backdoor behaviors, all geared towards reducing real-world risks from sophisticated AI systems.

About NudgeNudge is on a transformative mission to harness advanced technology that interfaces with the brain to enhance human life. Our pioneering focus is on creating a cutting-edge, non-invasive ultrasound device capable of stimulating and imaging the brain with unparalleled resolution. This initiative integrates innovative hardware, software, and research methodologies to develop life-changing products that can eventually benefit millions, if not billions, of individuals.About the RoleAs a Research Scientist specializing in Cell Biology at Nudge, you will:Innovate techniques to characterize the mechanisms by which ultrasound affects neural tissue.Design and conduct in vitro experiments to assess the influence of ultrasound on cellular characteristics, activity, and plasticity.Optimize ultrasound parameters to enhance cellular activity and promote plasticity.Translate findings from in vitro studies to guide human neuromodulation research.About YouWe are looking for research scientists at various stages of their careers. Regardless of your level, you should possess:A PhD or postdoctoral experience in neuroscience, molecular/cellular biology, biomedical engineering, or a related field.Expertise in neural cell culture or slice methodologies, with a preference for human neural iPSC techniques.Experience in calcium imaging, functional imaging analysis, two-photon microscopy, or other advanced imaging techniques.Proficiency in electrophysiology, voltammetry, or other neural recording methodologies.A proven track record of significant technical contributions.A commitment to high integrity and ethical research practices.

Join Mercor as a Data ScientistAt Mercor, we stand at the forefront of labor markets and artificial intelligence research. We collaborate with top-tier AI laboratories and businesses to infuse the human intelligence crucial for the evolution of AI.Our expansive talent network empowers frontier AI models, mirroring the way educators impart knowledge: sharing insights and experiences that transcend mere coding. Currently, our network boasts over 30,000 experts generating more than $2 million daily.We are pioneering a new work paradigm where specialized expertise drives AI progress. To realize this vision, we seek a dynamic, fast-paced, and dedicated team. You will collaborate with leading researchers, operators, and AI companies, playing a pivotal role in the systems that are reshaping society.As a profitable Series C company, Mercor is valued at $10 billion and operates from our new headquarters in San Francisco with an in-office work schedule five days a week.Your RoleIn your first year, you will implement analyses and experiments that enhance key product metrics, including match quality, time-to-hire, candidate experience, and revenue. Your responsibilities will include:Establishing north-star and feature-specific metrics for our ranking systems, interview analytics, and payout frameworks.Designing and executing A/B tests and quasi-experiments, translating results into product decisions within the same week.Creating source-of-truth dashboards and streamlined data models to enable teams to self-serve answers.Collaborating with engineers to instrument events, enhancing data quality and latency from ingestion to insights.Rapidly prototyping models (from baseline models to gradient boosting) to optimize matching and scoring.Assisting in the evaluation of LLM-powered agents through the design of rubrics, human-in-the-loop studies, and guardrail mechanisms.What Makes You a Great FitYou possess strong foundational skills in statistics, SQL, and Python, alongside projects you are eager to showcase. You adapt swiftly, frame inquiries, test hypotheses, and deliver results within a day, valuing clarity in communication as much as statistical significance. A keen interest in LLM evaluation, retrieval, and ranking is a plus; you will learn alongside professionals from renowned firms such as Jane Street, Citadel, Databricks, and Stripe.

At Sciforium, we are at the forefront of AI infrastructure, creating next-generation multimodal AI models and a proprietary high-efficiency serving platform. With substantial backing from AMD, our team is rapidly expanding to develop the complete stack necessary for cutting-edge AI models and real-time applications.About the RoleWe are on the lookout for a talented Senior Research Scientist with expertise in advanced AI and machine learning. This role entails spearheading innovative research projects focusing on large language models, generative media, model architecture, optimization, and scalable training systems. You will engage directly with contemporary ML frameworks, publish original research, and collaborate closely with engineering teams to transition impactful models into production. This position is perfect for a driven researcher excited about pioneering breakthroughs in AI.What You'll DoLead research initiatives in advanced machine learning topics such as LLMs, generative AI, foundational modeling, optimization strategies, diffusion models, and novel Transformer architectures.Design, implement, and assess new ML algorithms using frameworks like PyTorch and JAX.Conduct large-scale distributed training experiments utilizing multi-GPU/TPU systems and cutting-edge compute infrastructure.Enhance performance through debugging frameworks, optimizing speed, and refining training pipelines.Generate high-quality research outputs including academic papers, internal reports, patents, and reproducible code.Work collaboratively with engineering and product teams to convert research prototypes into robust production systems.Stay updated with the latest research advancements to incorporate state-of-the-art techniques into Sciforium's AI roadmap.Mentor junior researchers and actively contribute to fostering a world-class AI research culture.

Join our dynamic team at mindlance2 as an Associate Scientist. In this pivotal role, you will contribute to groundbreaking research and development projects, collaborating with a talented group of professionals dedicated to innovation and scientific advancement.As an Associate Scientist, you will engage in experimental design, data analysis, and interpretation of results, ensuring the highest standards of scientific integrity. This position offers an exciting opportunity to grow your skills and make significant contributions to our projects.

Join Mindlance as a Data Scientist, where you will leverage data to drive insights and support decision-making processes. You will be responsible for analyzing complex datasets, developing predictive models, and collaborating with cross-functional teams to enhance business strategies.

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.

At Genmo, we are pioneers in developing cutting-edge models for video generation, aiming to unlock the full potential of Artificial General Intelligence (AGI). Join our innovative team and play a vital role in redefining the landscape of AI technology.About the RoleWe are on the lookout for a talented Research Engineer to enhance our research team dedicated to advancing visual generative AI. In this role, you will collaborate with experienced professionals to refine and deploy generative models safely and effectively.What You'll DoDevelop novel machine learning techniques tailored for visual generative modeling.Experiment with diverse generative architectures including Diffusion Models, GANs, and Transformers.Optimize model performance and scalability.Ensure safe and robust deployment of models.Work collaboratively with cross-functional teams to integrate research advancements.Engage in research discussions and contribute to technical documentation.Required QualificationsBachelor's or Master's degree in Computer Science, Machine Learning, or a related field (recent graduates encouraged to apply).A minimum of 2 years’ experience in Machine Learning.Strong understanding of machine learning principles, particularly in generative models.Proficient programming skills in Python, along with frameworks like PyTorch or TensorFlow.Experience with deep learning frameworks and model training techniques.Familiarity with core concepts in computer vision and generative AI.Hands-on project experience (academic or personal) with generative models.Excellent communication skills and a collaborative spirit to thrive in a research team environment.Preferred QualificationsResearch projects or thesis work in the field of generative AI.Experience with various generative models such as:Diffusion ModelsGANsTransformer architecturesLarge Language Models

Join Perplexity as a Research Engineering Manager, where you will spearhead a team of exceptional AI researchers and engineers dedicated to crafting the advanced models that power our innovative products. Our talented team has pioneered some of the most sophisticated models in agentic research, query understanding, and other critical domains that demand precision and depth. As we broaden our user base and expand our product offerings, our proprietary models are increasingly essential for delivering a premium experience to the world's most discerning users.You will explore our extensive datasets of conversational and agentic queries, applying state-of-the-art training methodologies to enhance AI model performance. Through proactive technical and organizational leadership, you will empower your team to create cutting-edge models for the applications that are most significant to our business and our users.

About MercorMercor sits at the forefront of labor markets and artificial intelligence research, collaborating with premier AI laboratories and enterprises to harness the human intelligence crucial for AI evolution.Our expansive talent network empowers the training of cutting-edge AI models, akin to how educators impart knowledge to students—sharing insights, experiences, and contexts that transcend mere code. Currently, our network comprises over 30,000 experts, generating collective earnings exceeding $2 million daily.At Mercor, we are pioneering a unique category of work where expertise fuels AI progress. Realizing this vision necessitates a bold, fast-paced, and deeply dedicated team. You will collaborate with researchers, operators, and AI firms that are at the vanguard of transforming systems that redefine society.As a profitable Series C company, Mercor is valued at $10 billion and maintains an in-office presence five days a week at our new headquarters in San Francisco.About the RoleIn your capacity as a Research Engineer at Mercor, you will operate at the intersection of engineering and applied AI research. You will play a pivotal role in post-training and Reinforcement Learning from Human Feedback (RLVR), synthetic data generation, and large-scale evaluation workflows essential for advancing frontier language models.Your contributions will help train large language models to adeptly utilize tools, exhibit agentic behavior, and engage in real-world reasoning within production environments. You will be instrumental in shaping rewards, conducting post-training experiments, and constructing scalable systems to enhance model performance. Your responsibilities will also include designing and evaluating datasets, creating scalable data augmentation pipelines, and developing rubrics and evaluators that expand the learning potential of LLMs.

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.