Machine Learning Engineer

Build and deploy production machine learning systems for complex challenges in the electric grid while working across multiple ML domains.

Responsibilities

• Train machine learning models and deploy them into production environments
• Collaborate with senior teammates to develop enterprise-quality ML systems across multiple ML domains
• Operationalize end-to-end model training and serving at enterprise scale
• Stay current with latest advancements in machine learning and apply learnings to ongoing work

Requirements

• Master’s Degree or Bachelor's Degree in Machine Learning, Computer Science, Statistics, or a related field
• Experience in machine learning model development and engineering
• Expertise in one or more of the following areas:
  • Multimodal machine learning
  • Natural language processing (NLP)
  • Agentic AI
  • Planning, control and reinforcement learning
• Strong programming skills in Python
• Experience with ML frameworks such as PyTorch or TensorFlow
• Experience building and deploying ML systems at scale OR demonstrated ability to perform applied ML research and develop state of the art methods in an academic setting

Technologies

• Python
• PyTorch
• TensorFlow
• AWS
• GCP
• Azure

Benefits

• Competitive salary and equity
• Medical, dental, and vision coverage
• Generous PTO and a flexible hybrid work model
• 401(k) with employer contribution
• Professional development
• Opportunity to work on real-world problems within an Alphabet-backed environment

Nice to have

• PhD in Machine Learning, Computer Science, Statistics, or a related field
• Experience with cloud platforms such as AWS, GCP, or Azure
• A strong portfolio of projects demonstrating ML expertise

Location and Salary

• Mountain View, CA (hybrid)
• USD 166,000 - 244,000 per year

Our Values

• Take charge: initiative and ownership that move the mission forward
• Transform with purpose: build solutions that solve real problems and create meaningful impact
• Be a Tapestry, not a thread: collaborate across diverse skills and perspectives
• Always fine-tune: stay curious, seek feedback, and refine understanding as you learn
• Stay grounded: listen openly, value different perspectives, and focus on what matters most

Education: Master’s Degree/Bachelor's Degree in Machine Learning, Computer Science, Statistics or related field

Summary focus: building and deploying state of the art machine learning models using multimodal machine learning, information retrieval, NLP, and agentic AI to address challenges facing today’s electric grid.