Develop post-training recipes and build enterprise data agents for autonomous planning, code generation, and multi-step workflows. Requires 2+ years applied research experience shipping prototypes, plus expertise in LLMs, agents, and RL.

Researcher building frontier RL environments, evaluations, and training signals to steer OpenAI's largest agent training runs and measure model capabilities.

Build and deploy AI systems (LLMs, bandits) for monetization, balancing revenue and retention. Requires advanced ML degree or equivalent, applied large-model experience, and leadership skills.

Conduct research on training and scaling models for web indexing, focusing on convergence of search, recommendations, and transformer architectures. Requires deep intuition in modern ML models and a focus on applied research.

Leads the architecture, development, integration, and lifecycle ownership of autonomous behaviors and motion-planning software for unmanned platforms. Requires a relevant engineering degree, production C++ expertise, and at least seven years of experience in autonomy, planning, optimization, integration, or flight controls.

The Member of Technical Staff will train action policies and world models while tackling high-impact problems across research, engineering, and infrastructure. The role is flexible and matched to demonstrated technical strengths.

Build and deploy autonomous AI agents that navigate websites, execute workflows, and integrate with APIs and SaaS platforms using LLMs and browser automation tools.

Work as a fullstack applied researcher adapting multimodal video foundation models for production. Focus on controllability, personalization, and end-user quality using SFT, RL, and data-driven refinement.

Leads hands-on research and engineering to improve frontier language models for AI software engineering, owning experiments, evaluation, training, and optimization end to end. The role also mentors researchers and engineers and partners across research, product, and infrastructure teams.

Lead high-impact research on LLMs and agentic systems, driving post-training, reasoning, and evaluation to power enterprise AI deployments. Requires 7+ years ML research experience, PhD or equivalent, and strong publication record.

Leads broad, ambiguous technical charters for Rippling’s AI platform, designing and building scalable infrastructure, evaluation systems, model-related tooling, and reliable distributed services. Requires 14+ years of software engineering experience, deep backend or systems expertise, and strong hands-on coding and technical leadership.

Hands-on technical leader building reusable AI Platform infrastructure for agents, automation, evaluations, data pipelines, and reliable production systems. The role requires 10–15 years of software engineering experience, strong distributed-systems and architecture skills, and continued involvement in coding and technical execution.

Conduct research on autonomous AI agents and reinforcement learning to build self-improving systems that reason, code, and learn at scale within the Snowflake Data Cloud. Requires a PhD (or equivalent) and strong expertise in RL and agentic AI.

Post-doctoral researcher conducting independent and collaborative AI/ML research focused on high-impact domains like medicine, finance, and law. Requires a recent or imminent PhD and publications in top venues.

Graduate research intern (MS/PhD) building Customer World Models and proactive intelligence systems using representation learning, RL, and agentic decision-making. Own research end-to-end from framing to production deployment.

Leads original statistical machine learning research for financial market prediction and portfolio optimization while setting a team’s research agenda, mentoring researchers, and guiding projects through evaluation and productionization. Requires strong mathematical foundations, research leadership experience, and Ph.D.-level coursework.

Build next-generation training infrastructure for physical AI models that perceive, reason, and act in structured environments. Lead development of representation models, latent world models, and policy optimization systems.

Researcher developing and scaling architectures and optimization techniques for flagship large language models. The role requires experience contributing to major LLM training runs, strong knowledge of inference and Transformer efficiency, and an empirical approach to experiments and debugging.

Leads the design, development, integration, and field validation of tactical autonomy software for unmanned platforms across air, land, and sea domains. Requires 12+ years of industry experience, advanced engineering education, strong C++ and Python skills, and hands-on autonomy or robotics experience.

As a Research Engineer, you will conduct and enable cutting-edge research, translating it into the core product pipeline. You will develop and improve state-of-the-art data curation strategies, accelerating research and ensuring product innovation.

Leads research and productionization of diffusion, vision-language, and vision-language-action models for real-time robotic perception on construction sites. The role requires 8+ years of deep-learning R&D or an advanced degree with strong publications, plus expertise in scalable training and edge deployment.

Anthropic is seeking a Research Scientist to join their Life Sciences team. This role involves building and shipping agentic tools, designing evaluation benchmarks, and partnering with external users to improve model capabilities on scientific tasks.

As a Research Scientist II on the Video team, you will drive core research initiatives, deliver reproducible experimental results, and help translate machine learning models into real-world product solutions, focusing on real-time video processing and deepfake detection.

As a Simulation Researcher/Engineer, you will design and build simulation environments for training general-purpose robot policies. This role involves working with generative models and classical physics simulation, developing differentiable pipelines, and driving asset generation.

As a Research Scientist on the World Models team, you will invent next-generation world model architectures with a focus on controllability and physical consistency, develop controllability mechanisms, and define and own metrics for physical fidelity and action-following.

This is a research role focused on building models that continuously evolve with the world, with a focus on efficiency, gradient-free exploration, real-time learning, and interface design. The role requires strong programming skills and expertise in model optimization techniques.

Join the alignment research team to work on high-impact, under-resourced projects focused on AI alignment. This role requires strong ML research and Python skills to build, train, or evaluate deep learning models.

Voleon Securities is seeking an experienced and creative reinforcement learning researcher to join their ML research group. This role focuses on applying state-of-the-art AI/ML techniques to construct market-making strategies and optimize trading models.

As a Distinguished Architect, AI, you will be a technical multiplier for leading AI labs and AI-native companies, bridging their infrastructure aspirations with Datadog's technology roadmap. You will ensure the platform solves unique observability challenges for training and deploying foundational models at scale.

This role focuses on advancing how OpenAI builds and understands pretraining data at scale. The individual will treat data quality and curation as core research problems, developing new methods to select, combine, and transform data to improve model capabilities.

OpenAI is seeking a Research Engineer/Research Scientist to advance how the company prepares, curates, synthesizes, and understands multimodal data at scale. This role involves working on research and production problems related to synthesizing multimodal content, improving data pipelines, and building quality filters.

As a Staff Applied Scientist, you will define and build measurement systems for AI agent interfaces at Datadog, focusing on evaluation strategy, metric definition, and dataset creation to improve agent performance on customer workflows.

Conduct frontier AI research on LLMs, embedding models, and rerankers for RAG and semantic search. Requires PhD in CS or related field plus strong publication record in top ML venues.

Research intern focused on reinforcement learning for autonomous driving and robotics. Current PhD or MSc student in ML, CV, or robotics conducting novel RL research and publishing at top-tier conferences.

Research intern developing 3D vision and generation models (foundation models, Gaussian splatting, multi-modal pretraining) for autonomous driving and robotics. Requires current PhD/MSc studies in ML, CV/graphics, or robotics.

Lead Protege's DataLab research organization, defining strategy for AI training data quality, evaluation systems, and marketplace optimization while managing researchers and partnering with Product, Engineering, and GTM.

Lead a world-class research team advancing LLM scaling, post-training, RL, and inference efficiency at Databricks AI. Drive research roadmap and translate breakthroughs into production systems while collaborating closely with engineering and product teams.

Develop multi-agent AI architectures for enterprise coordination and collaborative reasoning. Requires research experience in MARL/GNNs, strong prototyping skills, and daily AI tool usage.

Develop and apply post-training methods and interpretability techniques to improve safety and understanding of frontier AI systems. Requires 3+ years of ML experience, expertise in RL techniques like RLHF and DPO, and published research in generative AI.

Leads research in multimodal audio-visual avatar generation for conversational AI, focusing on diffusion models, long-video synthesis, and integrating verbal/non-verbal signals. Requires PhD, 2-3+ years in generative models, PyTorch expertise, and top-tier publications.

Provides expert advisory on AI model behavior in finance, legal, or medical domains, collaborates on research tasks and publications, and engages in executive sales and GTM activities. Requires 5+ years top-tier experience and advanced degree (PhD/Masters/MD/JD).

Conducts cutting-edge research on AI models including LLMs, embedding models, and rerankers for information retrieval and agent paradigms. Requires PhD in CS or related field with strong ML, DL, and NLP background.

Applied Scientist drives research in efficient, adaptive ML including online learning and gradient-free methods, implements production ML systems, and shapes research/product roadmap. Requires 3-4 years ML experience deploying real-world systems.

Designs and authors context, procedures, skills, and system prompts for AI agents performing autonomous accounting tasks. Ensures consistency, monitors performance, and shapes future capabilities through precise language and systems thinking.

Conducts research to advance audio capabilities in AI models, designing and training large-scale multimodal systems, building audio data pipelines, and publishing findings. Requires ML expertise, Python proficiency, and experience with deep learning frameworks.

Conducts and publishes cutting-edge machine learning research, building and training large language models and contributing to applied AI product initiatives. Applicants should be pursuing a PhD or demonstrate exceptional equivalent experience, with expertise in ML systems, Transformers, programming, and modern ML frameworks.

Build and own the agent runtime, orchestration layer, and long-horizon coding agent workflows for an AI-driven consumer social platform.

Conducts research on foundation models for robotics, focusing on manipulation, sim-to-real transfer, RL, and skill learning using simulations and real robots. Requires PhD-level expertise in robotics/AI, strong publications, and software skills for open-source breakthroughs.

Conduct empirical research on AI's economic impacts, labor markets, and societal effects using external data and Python. Produce public outputs under mentorship, focusing on AI safety and policy recommendations; 4-month full-time program open to varying experience levels.

Leads research team advancing LLM scaling, post-training, RL, and inference efficiency. Drives innovations in optimization, distributed systems, and production integration using Python/PyTorch, with deep expertise in large-scale ML.