About The Position

Improve LLM capabilities influencing grounding data quality. Apply latest research to post-train LLMs. Build and evaluate metrics and reward models. Add new functionality and ensure high quality for customers using Copilot on their Business data. Design and implement scalable evaluation pipelines for LU and grounding quality Collaborate with cross-functional teams to define success metrics and drive continuous improvement in Copilot experiences

Requirements

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
  • Experience in Python, C# or similar programming languages for model development, training, and evaluation
  • Experience with large-scale machine learning systems, including training, fine-tuning, and deployment of LLMs or similar models
  • These requirements include but are not limited to the following specialized security screenings:
  • Hands-on experience with prompt engineering, reinforcement learning from human feedback (RLHF), or reward modeling
  • Familiarity with distributed systems and cloud platforms (e.g., Azure) for large-scale ML workloads
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