Machine Learning Engineer

About the Team

Tapestry is a division within Alphabet dedicated to creating an AI-driven electric grid. Our mission is to address critical infrastructure issues by making the energy system more transparent, reliable, cost-effective, plentiful, and sustainable. Originating from Alphabet's innovation hub, X, Tapestry unites specialists in energy, AI, software, engineering, and product development to deliver solutions enabling smarter planning, faster actions, and enhanced operation of the electricity ecosystem.

We operate globally, supporting partners in the US, UK, Chile, New Zealand, Australia, and Brazil, working towards a cleaner and more resilient energy future.

Joining Tapestry means being part of a multidisciplinary team engaged in impactful work on a worldwide scale.

Role Overview

We seek an early-career Machine Learning Engineer responsible for designing and deploying cutting-edge ML models to tackle complex challenges faced by the modern electric grid. This role involves collaborating with fellow ML Engineers, Data Scientists, and Software Engineers across diverse machine learning fields including multimodal ML, information retrieval, natural language processing, and agentic AI.

Key Responsibilities

• Develop, train, and deploy machine learning models in production settings.
• Collaborate with senior team members to create enterprise-level ML systems across various domains.
• Manage the operationalization of ML model training and deployment at scale.
• Keep current with the latest developments in machine learning.

Required Qualifications

• Master’s or Bachelor’s degree in Machine Learning, Computer Science, Statistics, or related disciplines.
• Hands-on experience in machine learning model development and engineering.
• Proficiency in one or more specializations such as multimodal ML, NLP, agentic AI, planning, control, or reinforcement learning.
• Strong programming capabilities in Python and familiarity with ML libraries such as PyTorch or TensorFlow.
• Experience in building and scaling ML systems in production, or demonstrated ability in conducting applied ML research and advancing state-of-the-art solutions in academic contexts.

Preferred Qualifications

• PhD in Machine Learning, Computer Science, Statistics, or related field.
• Experience working with cloud services like AWS, GCP, or Azure.
• A portfolio showcasing machine learning expertise through projects.

Core Values

• Take initiative and be accountable for driving mission progress.
• Create purposeful solutions that address meaningful problems.
• Collaborate with diverse skillsets to amplify impact as a cohesive team.
• Maintain curiosity, seek feedback, and continually refine understanding.
• Embrace openness, respect various viewpoints, and focus on key objectives.

Benefits and Culture

We foster a culture centered on growth, ownership, and impactful contributions, offering:

• Competitive compensation with salary and equity components.
• Comprehensive medical, dental, and vision insurance coverage.
• Generous paid time off and flexible hybrid work arrangements.
• 401(k) retirement plan including employer contributions.
• Opportunities for professional development.
• Engagement with significant real-world challenges backed by Alphabet’s resources.

Salary Information

The anticipated US base salary for this full-time role ranges from 166000 to 244000 USD per year, exclusive of bonuses, equity, and benefits. Individual salary depends on factors such as location, skills, experience, and education. Further compensation details will be provided during the hiring process.