Data & Machine Learning Researcher

About the Role

In this position, you will operate at the crossroads of research and practical engineering, exploring how cutting-edge Machine Learning techniques—including large language models (LLMs), reinforcement learning, and structured prediction—can enable autonomous decision-making in critical, high-impact areas. You will lead the research strategy for one or multiple product features, develop experimental frameworks, and collaborate closely with engineering teams to deliver results.

Key Responsibilities

• Design and execute thorough experiments on candidate model structures and decision-making algorithms.
• Convert research discoveries into production-quality prototypes and collaborate with MLOps teams for deployment.
• Analyze, summarize, and replicate pertinent academic and industrial research works.
• Develop evaluation tools, create benchmarks, and define metrics that accurately represent customer outcomes.
• Produce internal research documentation and contribute to external publications as appropriate.

Required Qualifications

• PhD or equivalent professional experience in machine learning, statistics, or another quantitative discipline.
• A proven publication record or evidence of impactful applied research implementations.
• Proficiency in PyTorch or JAX, with comfort in distributed training environments.
• Strong foundation in software engineering, able to evolve prototypes from notebooks into scalable services.
• Excellent technical communication skills with a systematic approach to mitigate risks through preliminary experiments.

Preferred Skills

• Experience with autonomous decision-making systems, Bayesian inference, or causal inference techniques.
• Hands-on expertise in deploying LLM-driven agents or systems that utilize external tools.