Member of Technical Staff - Machine Learning (ai Team)

Microsoft Microsoft · Big Tech · Mountain View, CA +4 · Software Engineering

This role focuses on developing and improving LLM models for general-purpose capabilities and products, with a strong emphasis on agentive experiences. Responsibilities include data acquisition/generation, generalizing ML solutions, leading evaluation efforts, adapting state-of-the-art research, and writing production-quality code. The role involves fine-tuning, training classifiers, and engineering prompts, aiming to push the boundaries of AI towards controllable, safety-aligned superintelligence.

What you'd actually do

  1. Leverage subject matter expertise to improve model quality for interactive and agentive experiences.
  2. Oversee data acquisition or generation efforts, ensuring that the data meets the model needs.
  3. Generalize machine learning (ML) solutions into repeatable frameworks.
  4. Lead evaluation efforts of models, including those deployed within Microsoft products and the Cloud API.
  5. Track advances in industry and academia, identifies relevant state-of-the-art research, and adapts algorithms and/or techniques to drive innovation and develop new solutions.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Nice to have

  • Doctorate in Computer Science, Machine Learning, Human-Centered AI or related field AND 2+ year(s) experience (e.g., finetuning models with supervision or reinforcement learning, understanding and fixing data quality and curation, working with collaborators on creating new products).
  • Master's Degree in Computer Science, Machine Learning, or related field AND 5+ years experience (e.g., managing structured and unstructured data, developing and debugging models, creating infrastructure for AI-powered products).
  • Bachelor's Degree in Computer Science, Mathematics, Machine Learning, Physics, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying machine learning techniques and driving product direction).
  • Demonstrated engineering experience or research experience (e.g. creating or leading the creation of a feature in a different company, complex graduate work, research papers, or other experience).
  • 4+ years of data science experience (e.g., managing structured and unstructured data, applying machine learning techniques and driving product direction).
  • Experience prompting, evaluating, and working with large language models.
  • Experience writing production-quality Python code.

What the JD emphasized

  • agentive
  • evaluating LLMs
  • fine tuning
  • training
  • production quality code
  • customer-facing features
  • interactive and agentive experiences
  • data acquisition or generation
  • evaluation efforts
  • state-of-the-art research
  • Humanist Superintelligence
  • ultra-capable systems that remain controllable, safety-aligned, and anchored to human values

Other signals

  • LLM models for general purpose capabilities
  • agentive
  • training
  • evaluating LLMs
  • production quality code
  • customer-facing features
  • reinforcement learning data
  • fine tuning
  • training classifiers
  • engineering prompts
  • Humanist Superintelligence
  • next generation of models