Research Engineer/Scientist
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Research Engineer / Scientist
Location: United States
Employment Type: Full-time
Focus: Frontier AI, Agentic AI, Reinforcement Learning, Computer Use, Multimodal Models, Long-Horizon Agents
About Our Client
Our client is a stealth-stage AI company building frontier models focused on human intent understanding, computer use, and autonomous agent systems.
The founding team includes leaders from Tesla AI, Google DeepMind, NVIDIA, Physical Intelligence, and Apple. They are building from the ground up and looking for early research talent to help shape the technical direction, research agenda, and product architecture from day one.
This is an opportunity to work on some of the hardest problems in applied AI: teaching agents to understand how people work, represent intent, use computers, and complete long-horizon tasks with increasing autonomy.
About the Role
Our client is hiring a Research Engineer / Scientist to own ambitious research bets end to end.
This person will work across hypothesis generation, data strategy, model training, evaluation, deployment, and iteration. The role is focused on reinforcement learning, post-training, continual learning, multimodal agents, and long-horizon autonomous systems.
The team is open to a range of backgrounds, from fresh PhD graduates with strong research internships to senior researchers who have led teams at top AI labs.
What You'll Do
Run experiments and train frontier AI models focused on human judgment scaling, computer use, and intent representation learning
Post-train LLMs and multimodal agents using reinforcement learning and continual learning methods
Work with large-scale screen recording and behavioral data to understand how individual users work
Build models that can learn user workflows and proactively automate tasks
Design and execute rigorous research experiments that improve autonomous agent capabilities
Own research bets end to end, from hypothesis and data through training, evaluation, deployment, and measurement
Help define the company's research direction as an early technical team member
Partner closely with founders and engineering leadership on technical architecture and product strategy
Translate cutting-edge research into systems that can power real product experiences
What We're Looking For
Experience in frontier AI research, applied AI research, or research engineering
Strong background in machine learning, deep learning, reinforcement learning, post-training, continual learning, or multimodal systems
Experience designing and running rigorous experiments
Ability to move from research idea to implemented system
Strong programming and engineering fundamentals
Comfort working with large-scale datasets and complex model training workflows
Strong judgment around model evaluation, data quality, experimental design, and deployment readiness
Ability to operate in ambiguity and take ownership of open-ended research problems
Clear communication and ability to collaborate with a small, high-caliber founding team
Excitement about computer use, autonomous agents, human intent modeling, and the future of AI-native software
Relevant Research Areas
Relevant experience may include:
Reinforcement learning
Post-training
Continual learning
Long-horizon agents
Computer use agents
Multimodal LLMs
Human behavior modeling
Intent representation learning
Human judgment scaling
Behavioral data modeling
Agent evaluation
AI automation
Large-scale model training
Ideal Background
Our client is open to a range of seniority levels, including:
Fresh PhD graduates with strong research internship experience
Research engineers from frontier AI labs
Applied scientists with experience training and evaluating advanced AI systems
Senior researchers who have led teams or major technical efforts
Builders who can connect research quality with production-minded execution
Why This Opportunity
Join a stealth-stage AI company at the founding team stage
Work directly with leaders from Tesla AI, Google DeepMind, NVIDIA, Physical Intelligence, and Apple
Help define the research agenda from day one
Own ambitious technical bets across reinforcement learning, post-training, continual learning, and agentic AI
Work on frontier problems in computer use, human intent understanding, and long-horizon autonomous agents
Build models that learn how people work and help automate real tasks
Shape both technical architecture and product direction early
Ideal Candidate Profile
The ideal candidate is a research-minded builder who wants to push the frontier of agentic AI.
They can design strong experiments, train models, reason dee