Member of Technical Staff - Post-training

Microsoft Microsoft · Big Tech · Redmond, WA +2 · Research Sciences

This role focuses on post-training methods for AI models, including continual pre-training, large-scale deep reinforcement learning, and data synthesis. The team works on language and multimodal models, with a focus on code-specific applications like Github Copilot. They also develop data infrastructure, tooling, and conduct research to improve model performance and impact. The role involves designing datasets, advancing model training, and ensuring data quality for cutting-edge AI.

What you'd actually do

  1. Design & Evaluate Datasets
  2. Advance Model Training
  3. Develop Data Infrastructure
  4. Data Quality & Analysis
  5. Tooling & Workflows

Skills

Required

  • Bachelor's Degree (complete or in progress) in relevant field AND 3+ months related research internship experience OR Master's Degree in relevant field OR equivalent experience
  • Software engineering skills with fluency in Python and modern data libraries

Nice to have

  • Master's Degree in relevant field AND 1+ year(s) related research experience OR equivalent experience
  • Coding expertise in Python and data libraries (Pandas, NumPy, etc.)
  • Proficiency with distributed data frameworks (Spark, Ray, Apache Beam) and cloud ecosystems (Azure, data lakes)
  • Hands-on experience with large-scale, unstructured or semi-structured datasets: images, video, audio, and code
  • Proven experience trai

What the JD emphasized

  • post-training methods
  • continual pre-training
  • large-scale deep reinforcement learning
  • curate and synthesize training data
  • fine-tuning approaches
  • language and multi-modality
  • code-specific models
  • Github Copilot
  • Visual Studio Code
  • code completion model
  • software engineering (SWE) agent models
  • LoRA
  • DeBerTa
  • Oscar
  • Rho-1
  • Florence
  • Phi models
  • AI Data & Training Technical Staff
  • creating world-class datasets
  • training front-tier models
  • developing scalable data pipelines
  • driving experiments
  • research, data engineering, and AI model training
  • Products
  • startup-style efficiency
  • practical problem-solving
  • continuous learning
  • changing priorities
  • creating meaningful impact
  • self-driven
  • write efficient code
  • debug training jobs
  • document findings
  • track record in these fields
  • Humanist Superintelligence
  • ultra-capable systems
  • controllable
  • safety-aligned
  • anchored to human values
  • amplify human potential
  • humanity remains firmly in control
  • benefit society
  • advancing science, education, and global well-being
  • partner with incredible product teams
  • reach billions of users
  • immense positive impact
  • brilliant, highly-ambitious and low ego individual
  • next generation of models

Other signals

  • post-training methods
  • continual pre-training
  • large-scale deep reinforcement learning
  • curate and synthesize training data
  • fine-tuning approaches
  • language and multi-modality
  • code-specific models
  • Github Copilot
  • Visual Studio Code
  • code completion model
  • software engineering (SWE) agent models
  • LoRA
  • DeBerTa
  • Oscar
  • Rho-1
  • Florence
  • Phi models
  • AI Data & Training Technical Staff
  • creating world-class datasets
  • training front-tier models
  • developing scalable data pipelines
  • driving experiments
  • research, data engineering, and AI model training
  • Products
  • startup-style efficiency
  • practical problem-solving
  • continuous learning
  • changing priorities
  • creating meaningful impact
  • self-driven
  • write efficient code
  • debug training jobs
  • document findings
  • track record in these fields
  • Humanist Superintelligence
  • ultra-capable systems
  • controllable
  • safety-aligned
  • anchored to human values
  • amplify human potential
  • humanity remains firmly in control
  • benefit society
  • advancing science, education, and global well-being
  • partner with incredible product teams
  • reach billions of users
  • immense positive impact
  • brilliant, highly-ambitious and low ego individual
  • next generation of models
  • Design & Evaluate Datasets
  • Build high-quality datasets and benchmarks for training AI models
  • run ablation studies to measure impact and optimize data effectiveness
  • Advance Model Training
  • Apply deep expertise in pre-training, post-training, and reinforcement learning (RL) for both language and multimodal models
  • Develop Data Infrastructure
  • Create and maintain scalable pipelines for ingestion, preprocessing, filtering, and annotation of large, complex datasets
  • Data Quality & Analysis
  • Assess real-world multimodal datasets (text, image, video, audio, code) for quality, diversity, and relevance
  • identify gaps and propose improvements
  • Tooling & Workflows
  • Build lightweight tools for dataset auditing, visualization, and versioning to streamline experimentation
  • Research & Innovation
  • Collaborate with cross-functional teams to push research and product boundaries
  • delivering models that make a real-world impact
  • Bachelor's Degree (complete or in progress) in relevant field AND 3+ months related research internship experience OR Master's Degree in relevant field OR equivalent experience
  • Software engineering skills with fluency in Python and modern data libraries
  • The ability to meet Microsoft, customer and/or government security screening requirements are required for this role
  • Microsoft Cloud Background Check
  • Master's Degree in relevant field AND 1+ year(s) related research experience OR equivalent experience
  • Coding expertise in Python and data libraries (Pandas, NumPy, etc.)
  • Proficiency with distributed data frameworks (Spark, Ray, Apache Beam) and cloud ecosystems (Azure, data lakes)
  • Hands-on experience with large-scale, unstructured or semi-structured datasets: images, video, audio, and code
  • Proven experience trai