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ModeRemote92 Hybrid95 On-site72 Location TBD213

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11 of 472 matching

Research Engineer - Cybersecurity (RL Environments)
Mistral
Paris, France (Remote)
1d agoNew
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San Francisco, California, United States (On-site)
1d agoNew
Research Engineer, AI for Chip Design
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San Francisco, California, United States (Remote)
$380k–$500k/yr
1d agoTop pickNew
Senior ML Engineer (AI Research, Physical AI)
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Israel; Remote (Europe); United Kingdom (Remote)
1d agoNew
Senior ML Researcher
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European Union (Remote)
1d agoNew
Senior ML Engineer (AI Research/ Portability)
Nebius
Israel; Remote (Europe); United Kingdom (Remote)
1d agoTop pickNew
Software Engineer, RL Data
Cursor
San Francisco, California, United States (On-site)
1d agoTop pickNew
Research Scientist - Human-AI Systems
Snorkel AI
San Francisco, CA, United States; New York, NY, United States; Remote (Remote)
$200k–$375k/yr
1d agoNew
Research Engineer, Takeoff Intel
Anthropic
San Francisco, CA, United States (Hybrid)
$350k–$850k/yr
1d agoNew
Research Engineer, Cybersecurity RL (Reinforcement Learning)
Anthropic
Zürich, Switzerland (Hybrid)
1d agoTop pickNew
Staff / Principal Applied AI Researcher (Agentic Search)
Nebius
Zurich, Switzerland
1d agoTop pickNew

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Applied researchTop pickNew

Software Engineer, RL Data

CursorSan Francisco, California, United States (On-site)

Posted 1d ago/Full-time/Expires Nov 10, 2026

Apply on company site Original posting

Why it matters

The role directly shapes frontier coding-agent capability through task design, rewards, training environments, trace analysis, and evaluations. It focuses on converting real-world agent failures into reusable datasets and tools, with ownership over what agents learn and how progress is measured.

About the job

Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.

Software Engineer, Reinforcement learning

SpaceXAI is building the future of coding. We train frontier coding agents and scale RL on real user data to make them increasingly effective.

About the role

As a Software Engineer on the RL Data team at SpaceXAI, you'll create the tasks, rewards, and environments that train our coding agents. The team owns the data that goes into training: what the model is asked to do, how we score it, and the setups it learns in.

What you’ll do

Designing a task set that teaches a specific agent capability, then iterating on it from traces and evals until the model actually gets better.
Reading a pile of agent traces, finding a failure mode or a surprising behavior, and building a system that surfaces more of the same.
Turning a one-off recipe into something other teams can reuse: better rewards, cleaner environments, tighter data quality.
Partnering with research on whether a dataset is actually teaching the thing we think it is.

You may be a fit if

You write careful, fast code and have strong software engineering fundamentals.
You like setting tasks: breaking a fuzzy capability into something concrete you can measure.
You have an infra, data, or distributed systems background. RL experience is a plus, not a requirement.
You enjoy looking at messy real-world agent behavior and turning it into a dataset or a tool.

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