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.
Senior individual contributor building and deploying large-scale multimodal foundation models that integrate wearable sensor, biomarker, and behavioral data for personalized health insights.
Lead the design and validation of trustworthy benchmarks and evaluations for frontier AI models, including agentic and domain-specific tasks. Own the science of evals and annotator quality, publishing research and translating findings into production datasets.
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 on pre-training methodologies for large AI models, develops new architectures and data strategies, runs large-scale experiments, and publishes findings. Requires strong ML fundamentals, Python proficiency, and experience with deep learning frameworks.
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.
Leads research team advancing LLM scaling, efficiency, post-training, RL, and inference optimization. Drives innovations from research to production, requiring deep ML expertise, Python/PyTorch proficiency, and leadership in large-scale experiments.
Senior researcher studies how training choices shape aligned behavior in frontier models, developing synthetic data, evaluation loops, and experiments to ensure durable, robust tendencies like honest reasoning and instruction-following.
Develops and trains large-scale diffusion models for generating 3D worlds, incorporating novel control signals and integrating cutting-edge generative AI research into production. Requires 3+ years in generative modeling, PyTorch/TensorFlow expertise, and strong publication record.
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.
Designs worst-case demonstrations and adversarial evaluations to uncover AGI misalignment risks like deception and power-seeking. Builds automated stress-testing infrastructure and researches alignment failure modes to inform OpenAI's safety strategy. Requires 4+ years in AI red-teaming or adversarial ML.
Designs and runs experiments to improve AI model intent alignment, honesty, calibration, and robustness using RL and empirical ML methods. Trains/evaluates large models like LLMs and integrates techniques into production workflows.
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.
Postdoctoral researcher leading high-impact AI projects on Mixture-of-Experts and long-context language models, training/releasing models, building open-source tools, publishing papers, and mentoring juniors. Requires recent PhD in CS/ML with strong publication record and PyTorch expertise.
Leads foundational research on agentic AI systems for scientific reasoning, including literature synthesis, hypothesis formation, coding, experiments, and data analysis. Requires PhD in ML/NLP/reasoning with expertise in language models or reinforcement learning.
AI Researcher develops and fine-tunes large multimodal models for real-time conversational avatars, modeling verbal/non-verbal behaviors with low latency. Requires PhD or equivalent, hands-on experience with VLMs, PyTorch, and deep learning.
Conducts research on world-action foundation models for robotics and autonomous driving, focusing on 3D vision, multi-modal pretraining, and Gaussian splatting. Requires MSc/PhD in ML/CV, strong publication record, and expertise in Python/PyTorch.
Conducts cutting-edge research in 3D vision, reconstruction, and generation for autonomous driving and robotics, publishes at top conferences, and deploys algorithms to production systems. Requires MSc/PhD in ML/CV, strong publication record, and expertise in Python, PyTorch, CV, and robotics.
Develops next-generation multimodal LLMs integrating speech, text, tools, and real-time reasoning for conversational AI agents. Requires strong background in LLMs, multimodal models, fast experimentation, and production deployment experience.
Research Scientist investigates training data interventions to improve deep learning model quality and behavior. Sources ideas from literature, conducts customer-grounded research, and collaborates with engineers to deliver impact. Requires 3+ years deep learning research and PyTorch proficiency.
Conducts foundational research and develops scalable ML models for speech-to-text, text-to-speech, and neural audio codecs in real-time voice AI agents. Requires deep expertise in voice modeling, self-supervised learning, and production deployment at enterprise scale.
Designs novel AI models and training methodologies from first principles on wafer-scale hardware, integrating computational science techniques. Requires PhD-level expertise in ML or related fields, strong publication record, and proficiency in PyTorch/Python.
Leads original research in action-conditioned world models, physical AI, and generative modeling for embodied systems. Requires PhD in ML/CS/Robotics with top publications and expertise in generative models and large-scale training.
Leads research in computer vision, multimodal understanding, and visual generation. Develops novel models and methodologies, translates research to production, and mentors teams. Requires PhD preferred, 8+ years experience, and expertise in PyTorch, TensorFlow, transformers.
Conducts ML research to advance LLMs and audio models for real-time voice AI agents, focusing on reasoning, latency, and conversational quality. Prototypes models, designs evaluations, and bridges research to production systems requiring strong PyTorch expertise and experimental mindset.
Owns mid-training for LLMs, optimizing data mixes, synthetic data pipelines, annealing schedules, and context extension to enhance reasoning, coding, and math capabilities for AI agents. Requires deep LLM pipeline expertise, hands-on large model training, and original research contributions.
AI Research Resident collaborates on research projects developing benchmarks and environments for long-horizon AI agents, identifying model failure modes, and training autonomous agents. Requires current MS/PhD enrollment, RL experience, systems engineering, and strong publications.
Conducts applied research on long-horizon autonomous AI agents, focusing on evaluation, post-training, environment design, and benchmarks to improve frontier models. Builds simulations, runs experiments, ships production code, and publishes findings.
Designs datasets and evaluation frameworks for frontier AI models, collaborating with top labs to expose failure modes, refine RLHF/RLVR pipelines, and measure data impact on capabilities. Requires strong quantitative skills, familiarity with LLM training, and research experience up to master's level.
Design and run SFT/RL experiments to measure dataset impact on LLM performance, capabilities, and alignment. Collaborate with labs to provide evidence of improvements; requires strong LLM training knowledge and fast experimentation, ideally undergrad/master's research background.
Forward Deployed Research Scientist collaborates with frontier AI labs on data strategies, fine-tunes open-weight LLMs, runs ablation studies, and validates data impact for client projects. Requires MS/PhD in ML/NLP/CS, hands-on LLM fine-tuning, and fast-paced experimental rigor.
Fellows conduct research and development in reinforcement learning to advance AI systems. Requires strong RL background and Python proficiency for collaborative program projects.
Fellows conduct research on AI safety, collaborating with Anthropic researchers to develop evaluation methods and alignment techniques. Requires strong interest in AI safety, CS/math background, and ML experience.
Develops state-of-the-art VQA systems for medical records using advanced NLP and CV techniques to achieve expert-level accuracy in document analysis. Requires deep expertise in NLP/CV, strong software engineering, and ability to work with noisy data in healthcare domain.
Develops state-of-the-art Visual Question Answering systems for medical records using advanced NLP and Computer Vision techniques. Requires expertise in these fields, strong software engineering skills, and ability to work with noisy data to achieve production-scale model performance.
Develops and deploys vision-language-action models and world models for autonomous robot finishing tasks in construction. Owns full lifecycle from data collection via teleoperation to edge deployment on Jetson hardware, requiring strong ML on robotics experience.
Conducts fundamental research on data-efficient ML architectures, including bootstrapped program synthesis and self-synthesizing learning systems. Requires Master's in ML/math, PyTorch fluency, and research experience.
Leads research in agentic AI and LLMs, developing models for enterprise reasoning, autonomous agents with tool use, and production systems. Requires PhD, expertise in LLM training/fine-tuning, agent systems, and technical leadership.
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.
Senior individual contributor building and deploying large-scale multimodal foundation models that integrate wearable sensor, biomarker, and behavioral data for personalized health insights.
Lead the design and validation of trustworthy benchmarks and evaluations for frontier AI models, including agentic and domain-specific tasks. Own the science of evals and annotator quality, publishing research and translating findings into production datasets.
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 on pre-training methodologies for large AI models, develops new architectures and data strategies, runs large-scale experiments, and publishes findings. Requires strong ML fundamentals, Python proficiency, and experience with deep learning frameworks.
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.
Leads research team advancing LLM scaling, efficiency, post-training, RL, and inference optimization. Drives innovations from research to production, requiring deep ML expertise, Python/PyTorch proficiency, and leadership in large-scale experiments.
Senior researcher studies how training choices shape aligned behavior in frontier models, developing synthetic data, evaluation loops, and experiments to ensure durable, robust tendencies like honest reasoning and instruction-following.
Develops and trains large-scale diffusion models for generating 3D worlds, incorporating novel control signals and integrating cutting-edge generative AI research into production. Requires 3+ years in generative modeling, PyTorch/TensorFlow expertise, and strong publication record.
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.
Designs worst-case demonstrations and adversarial evaluations to uncover AGI misalignment risks like deception and power-seeking. Builds automated stress-testing infrastructure and researches alignment failure modes to inform OpenAI's safety strategy. Requires 4+ years in AI red-teaming or adversarial ML.
Designs and runs experiments to improve AI model intent alignment, honesty, calibration, and robustness using RL and empirical ML methods. Trains/evaluates large models like LLMs and integrates techniques into production workflows.
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.
Postdoctoral researcher leading high-impact AI projects on Mixture-of-Experts and long-context language models, training/releasing models, building open-source tools, publishing papers, and mentoring juniors. Requires recent PhD in CS/ML with strong publication record and PyTorch expertise.
Leads foundational research on agentic AI systems for scientific reasoning, including literature synthesis, hypothesis formation, coding, experiments, and data analysis. Requires PhD in ML/NLP/reasoning with expertise in language models or reinforcement learning.
AI Researcher develops and fine-tunes large multimodal models for real-time conversational avatars, modeling verbal/non-verbal behaviors with low latency. Requires PhD or equivalent, hands-on experience with VLMs, PyTorch, and deep learning.
Conducts research on world-action foundation models for robotics and autonomous driving, focusing on 3D vision, multi-modal pretraining, and Gaussian splatting. Requires MSc/PhD in ML/CV, strong publication record, and expertise in Python/PyTorch.
Conducts cutting-edge research in 3D vision, reconstruction, and generation for autonomous driving and robotics, publishes at top conferences, and deploys algorithms to production systems. Requires MSc/PhD in ML/CV, strong publication record, and expertise in Python, PyTorch, CV, and robotics.
Develops next-generation multimodal LLMs integrating speech, text, tools, and real-time reasoning for conversational AI agents. Requires strong background in LLMs, multimodal models, fast experimentation, and production deployment experience.
Research Scientist investigates training data interventions to improve deep learning model quality and behavior. Sources ideas from literature, conducts customer-grounded research, and collaborates with engineers to deliver impact. Requires 3+ years deep learning research and PyTorch proficiency.
Conducts foundational research and develops scalable ML models for speech-to-text, text-to-speech, and neural audio codecs in real-time voice AI agents. Requires deep expertise in voice modeling, self-supervised learning, and production deployment at enterprise scale.
Designs novel AI models and training methodologies from first principles on wafer-scale hardware, integrating computational science techniques. Requires PhD-level expertise in ML or related fields, strong publication record, and proficiency in PyTorch/Python.
Leads original research in action-conditioned world models, physical AI, and generative modeling for embodied systems. Requires PhD in ML/CS/Robotics with top publications and expertise in generative models and large-scale training.
Leads research in computer vision, multimodal understanding, and visual generation. Develops novel models and methodologies, translates research to production, and mentors teams. Requires PhD preferred, 8+ years experience, and expertise in PyTorch, TensorFlow, transformers.
Conducts ML research to advance LLMs and audio models for real-time voice AI agents, focusing on reasoning, latency, and conversational quality. Prototypes models, designs evaluations, and bridges research to production systems requiring strong PyTorch expertise and experimental mindset.
Owns mid-training for LLMs, optimizing data mixes, synthetic data pipelines, annealing schedules, and context extension to enhance reasoning, coding, and math capabilities for AI agents. Requires deep LLM pipeline expertise, hands-on large model training, and original research contributions.
AI Research Resident collaborates on research projects developing benchmarks and environments for long-horizon AI agents, identifying model failure modes, and training autonomous agents. Requires current MS/PhD enrollment, RL experience, systems engineering, and strong publications.
Conducts applied research on long-horizon autonomous AI agents, focusing on evaluation, post-training, environment design, and benchmarks to improve frontier models. Builds simulations, runs experiments, ships production code, and publishes findings.
Designs datasets and evaluation frameworks for frontier AI models, collaborating with top labs to expose failure modes, refine RLHF/RLVR pipelines, and measure data impact on capabilities. Requires strong quantitative skills, familiarity with LLM training, and research experience up to master's level.
Design and run SFT/RL experiments to measure dataset impact on LLM performance, capabilities, and alignment. Collaborate with labs to provide evidence of improvements; requires strong LLM training knowledge and fast experimentation, ideally undergrad/master's research background.
Forward Deployed Research Scientist collaborates with frontier AI labs on data strategies, fine-tunes open-weight LLMs, runs ablation studies, and validates data impact for client projects. Requires MS/PhD in ML/NLP/CS, hands-on LLM fine-tuning, and fast-paced experimental rigor.
Fellows conduct research and development in reinforcement learning to advance AI systems. Requires strong RL background and Python proficiency for collaborative program projects.
Fellows conduct research on AI safety, collaborating with Anthropic researchers to develop evaluation methods and alignment techniques. Requires strong interest in AI safety, CS/math background, and ML experience.
Develops state-of-the-art VQA systems for medical records using advanced NLP and CV techniques to achieve expert-level accuracy in document analysis. Requires deep expertise in NLP/CV, strong software engineering, and ability to work with noisy data in healthcare domain.
Develops state-of-the-art Visual Question Answering systems for medical records using advanced NLP and Computer Vision techniques. Requires expertise in these fields, strong software engineering skills, and ability to work with noisy data to achieve production-scale model performance.
Develops and deploys vision-language-action models and world models for autonomous robot finishing tasks in construction. Owns full lifecycle from data collection via teleoperation to edge deployment on Jetson hardware, requiring strong ML on robotics experience.
Conducts fundamental research on data-efficient ML architectures, including bootstrapped program synthesis and self-synthesizing learning systems. Requires Master's in ML/math, PyTorch fluency, and research experience.
Leads research in agentic AI and LLMs, developing models for enterprise reasoning, autonomous agents with tool use, and production systems. Requires PhD, expertise in LLM training/fine-tuning, agent systems, and technical leadership.