Applied Research Engineer, Agents
Develops frameworks, data pipelines, and benchmarks for autonomous AI agents using SFT and RL. Collaborates with frontier AI labs, publishes research, and requires Master's/PhD plus 3+ years ML experience with deep learning proficiency.
Responsibilities
- Create frameworks and tools to construct, train, benchmark and evaluate autonomous agent capabilities.
- Design agent-focused data programs using supervised fine-tuning (SFT) and reinforcement learning (RL) methodologies.
- Develop data pipelines from diverse sources like code repositories, web browsers, and computer systems.
- Implement and adapt popular open-source agent libraries and benchmarks with proprietary datasets and models.
- Engage with research teams in frontier AI labs and the wider AI community to understand evolving agent data needs for frontier models and share best practices.
- Collaborate closely with frontier AI lab customers to understand requirements and guide model development.
- Publish research findings in academic journals, conferences, and blog posts.
Requirements
- Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or related field.
- At least 3 years of experience addressing sophisticated ML problems with successful delivery to customers.
- Experience building and training autonomous agents—tool use, structured outputs, multi-step planning—across browsers/GUI, codebases, and databases using SFT and RL.
- Constructed and evaluated agentic benchmarks (e.g. SWE-bench, WebArena, τ-bench, OSWorld) and reliability/efficiency suites (e.g. WABER).
- Adept at interpreting research literature and quickly turning new ideas into prototypes.
- Deep understanding of frontier models (autoregressive, diffusion), post-training (SFT, RLVR, RLAIF, RLHF, et al.), and their human data requirements.
- Proficient in Python, data science libraries and deep learning frameworks (e.g., PyTorch, JAX, TensorFlow).
- Strong analytical and problem-solving abilities in ambiguous situations.
- Excellent communication skills.
- Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.).
Compensation
- Annual base salary range: $250,000—$300,000 USD
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