Research Engineer
About the role
Research Engineer focused on building post-training pipelines, infrastructure for training environments, evaluation harnesses, and data curation systems to deploy and scale ML models and agents.
Responsibilities
- Build and own the pipelines behind our post-training runs, from data ingestion through deployment.
- Turn research prototypes into reliable, repeatable systems that run against production data.
- Build infrastructure for generating, scaling, and versioning training environments and evals.
- Develop the tooling that feeds the learning loop: searching traces, mining them for signal, labeling and curating data.
- Build the instrumentation we use to inspect, debug, and understand training runs.
- Work with researchers to co-design methods and systems, and with product engineers to ship what comes out.
Qualifications
- Excellent software engineering fundamentals paired with genuine ML depth. You've trained models yourself, end to end.
- Hands-on experience with distributed training, high-throughput data systems, or running large fleets of experiments.
- Fluency in Python and PyTorch, JAX, or similar.
- You can take a paper or a rough prototype and turn it into something shippable.
- Prior work on RL environments, evals, or data quality systems is a strong plus.
- Organized under load. You keep several workstreams coherent without dropping rigor.
- Bias toward ownership: you take a system from idea to production and stay responsible for it.
Skills
About ThirdLayer
Building Dex, the AI Browser Copilot
ThirdLayer is an applied research and product lab building the next interface for human–AI collaboration. Our first product is Dex, an AI copilot for the browser. Think Cursor for knowledge work, optimized for speed and embedded directly where you work. Most web agents are built for set-and-forget tasks. But real work is fluid and messy—spread across tabs, tools, and evolving decisions. Dex transforms your browser into an intelligent, multimodal workspace that understands your intent through voice, text, and action. It enhances familiar interfaces, automates tedious steps, and removes the friction of handoffs. Beneath the surface, Dex is more than a browser agent — it’s a foundation for: ● Long-term, cross-modal memory grounded in real workflows ● A new interaction layer to replace static UI with a collaborative canvas ● Personalization: understanding how individuals approach tasks and navigate software We're building the infrastructure for adaptive, intent-aware systems that work the way you do.
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