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AI Researcher - Post-Training

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Likely real

  • 107 open roles at this company in 30 days (mass-hiring blitz)
  • no salary disclosed (correlates with ghost postings)

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About the role

What you will do

Outcome Driven Development: Work in a team developing and implementing advanced products that enable customers to post-train models to power their agentic coding practices. These agents need to generate high-quality code that meets their enterprise standards and software development best practices.

Translate Prototypes to Products: Collaborate closely with researchers, research engineers, MLOps and engineers within the team to design hypotheses and experiments, iterate proofs-of-concept quickly and develop successful prototypes into cutting-edge products.

Subject Matter Expert: You will contribute and discuss ideas within our cross-disciplinary team, driving towards the next generation of coding model post-training for enterprises.

Spearhead Research & Innovation: Stay up-to-date with the latest LLM and agentic developments; you are driven by learning and teaching others. You will need to explain complex technical details and concepts to both technical and non-technical audiences.

Experience and qualifications

The ideal candidate will have

An advanced academic background (Master’s or PhD) in Computer Science, Machine Learning, or a related quantitative field.

4+ years industry experience in machine learning, with a solid understanding of modern software engineering practices and tools.

Fluency with Python including core ML frameworks, experience with Rust or any of SonarQube’s flagship languages (C#, C++, JS/TS, Java) is a plus.

Expertise in post-training of large language models, including:

Policy optimization algorithms (e.g. GRPO, PPO)

Verifier-based RL frameworks (RLVR)

Supervised fine-tuning (SFT)

Data-centric AI methods, including synthetic data and curation

Parameter-efficient fine-tuning (PEFT)

Preference and Safety Alignment

Experience of driving research projects, delivering valuable findings and prototypes, and then converting them into products.

Excellent communication skills in English and a talent for explaining complex scientific topics clearly and concisely.

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