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.

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.

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.

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.

Conduct original ML/AI research focused on large-scale foundation models and generative AI to advance Spotify's personalization systems like Discover Weekly. Requires PhD or Master's with publication track record in top conferences, 2+ years research experience, and expertise in recommender systems or representation learning.

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 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.

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 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 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.

Designs evaluation measures, harnesses, and datasets to assess risks from frontier AI systems, including dangerous capabilities testing. Collaborates with agencies, publishes methodologies for policymakers; requires 3+ years ML experience and publications in generative AI.

Designs methods, systems, and experiments for AI controls and monitoring to ensure alignment in high-stakes environments, including real-time tracking, fail-safes, and red-team simulations. Requires 3+ years ML experience, published research in generative AI, and strong prototyping skills.

Research Scientist focuses on agent robustness, developing tests, exploits, and mitigations for safe AI agents. Requires 3+ years ML experience, RL techniques like RLHF/DPO, and published research in generative AI.

Conducts research on post-training methodologies and performant inference for AI models, balancing pure research with applied work for production systems. Requires PhD in ML with top publications and ability to design rigorous experiments at scale.

Conducts research on efficient AI systems focusing on real-time adaptation, model efficiency, and cross-stack optimization. Requires PhD or equivalent, 4-5+ years industry experience, and deep ML expertise including PyTorch/JAX and optimization techniques.

Conduct research and build foundational ML models for structured and tabular data, combining statistical learning theory, probabilistic modeling, and large-scale systems. Requires a PhD and strong experience in tabular/relational ML.

Develops RLHF and post-training methods for personalized, multimodal AI systems on consumer devices, focusing on reward modeling, preference learning, long-horizon evaluation, and alignment with user values. Requires strong ML research background in RLHF and related areas.

Builds macroeconomic models and scenario-based forecasting tools for transformative AI impacts on growth, labor markets, and income distribution. Requires PhD in Economics, expertise in macro modeling, computational methods, and grounding in real-world AI usage data.

Part-time AI Trainer annotates mortgage conversation data, provides feedback on AI responses, and tests system quality for mortgage servicing calls. Requires 5+ years mortgage customer service experience and industry knowledge.

The Senior Applied Researcher develops and evaluates AI/ML model systems for healthcare SaaS products, working with structured and unstructured clinical data. The role requires advanced graduate education, industry healthcare ML experience, and hands-on expertise in LLMs, cloud platforms, data engineering, and production deployment.

Senior Applied Researcher develops AI/ML solutions for healthcare challenges, applying GenAI, LLMs, and techniques like RAG to build production-ready models in SaaS environments. Requires Master's in relevant field, healthcare data experience, Python proficiency, and ML frameworks expertise.

Conducts core research on multimodal foundation models for world-simulations, bridging modeling, data, systems, and evaluation. Requires advanced degree in CS/ML, first-principles scaling intuition, and experience with large-scale GPU training.

Develops bi-directional/recurrent architectures for hierarchical sensorimotor perception inspired by brain principles to advance AGI. Requires PhD-level expertise in deep learning frameworks like PyTorch/JAX, theoretical rigor, and passion for biological intelligence.

Conducts fundamental research on hierarchical RL agents, developing architectures for world modeling, planning, and ethologically constrained learning. Collaborates cross-functionally to translate brain-inspired principles into scalable AGI systems; requires PhD-level expertise in AI/ML and strong coding skills.

Conducts fundamental research on brain-inspired world models and AGI architectures, designing experiments on cognition, causal representations, and unsupervised learning. Collaborates with neuroscientists and engineers; requires PhD-level expertise in deep learning frameworks like PyTorch/JAX.

Conducts fundamental research on neuroscience-inspired energy-based models and hierarchical latent variable models for AGI. Designs experiments on cognition and collaborates cross-functionally to build scalable systems. Requires PhD-level expertise in deep learning and PyTorch/JAX.

Develops AI/ML models to transform sensor data into personalized health and sleep insights, focusing on thermoregulation, foundation models, and behavioral simulations using vast sleep datasets. Requires PhD in ML/AI-related field, 3+ years practical ML experience, and strong publications.

Leads R&D on small language models and AI training, developing efficient architectures, optimizing performance, and ensuring safety. Collaborates with research, engineering, and product teams using Python, PyTorch, TensorFlow, or JAX.

Build AI systems, agent harnesses, evaluation pipelines, retrieval infrastructure, crawling systems, and inference APIs that make subjective design quality measurable. The role requires experience building AI-forward products or systems, strong technical judgment, and comfort solving ambiguous startup problems.

Build state-of-the-art ML models to predict traffic behavior for autonomous driving, using generative sequence modeling and controllable agents for planning and simulation. Requires PhD preferred, 2+ years deploying ML systems, and expertise in PyTorch and robotics ML.

Collaborate on high-impact AI research projects, design and review deep learning models in PyTorch, analyze GPU performance, and co-author publications. Requires PhD in CS/AI/ML and hands-on expertise with Transformers, CNNs, and diffusion models.

Develops next-gen Agent RL training platform for enterprise GenAI, integrating cutting-edge research to train state-of-the-art models for complex use cases. Requires 5+ years LLM production experience, RLHF expertise, recent top publications, and advanced CS degree.

Develops and deploys state-of-the-art ML models and agents for enterprise GenAI using RL training and post-training algorithms. Requires 1-3 years LLM production experience, RLHF expertise, recent top publications, and advanced CS degree.

Develops and optimizes post-training algorithms for agent RL platforms, focusing on LLM training, inference frameworks, and multi-agent systems. Requires 1-3 years production LLM experience, expertise in PyTorch/CUDA, RLHF/PPO, and advanced degree.

Conducts cutting-edge research on data for state-of-the-art AI agents like browser and SWE agents, develops prototypes using LLMs and frameworks like PyTorch/JAX, and publishes in top ML venues. Requires 3+ years ML experience and strong cross-functional communication.

Research Engineer optimizes and scales production pretraining of frontier AI models, handling performance, debugging, experiments, and on-call incidents. Requires expertise in JAX, TPU, PyTorch, or large-scale ML systems with a 50/50 research-engineering balance.

Research Engineer focused on mechanistic interpretability, building tools and infrastructure to reverse-engineer neural networks for safer AI. Requires 5+ years software experience, Python proficiency, and AI research contributions.

Builds large-scale infrastructure for AI scientist training, evaluation, and deployment, resolving bottlenecks in distributed systems for scientific AGI. Requires 6+ years in infrastructure engineering with expertise in ML stacks, containers, and data pipelines.

Builds next-generation training environments and evaluations for agentic AI models, blending research in reinforcement learning with robust engineering implementation. Requires strong technical judgment, agency, and experience in ML systems.

Research Engineer implements and scales post-training techniques like Constitutional AI and RLHF for production AI models, optimizing capabilities, alignment, and safety. Requires strong Python skills, ML systems experience, and ability to handle complex distributed training pipelines.

Research Engineer works end-to-end to remove bottlenecks toward scientific AGI, focusing on long-horizon reasoning, computer use, and model capabilities. Requires 8+ years ML experience, expertise in language model pipelines, distributed systems, and collaborative problem-solving.