Machine Learning Engineer, Tapestry

Tapestry • Mountain View, CA

3d • Hybrid

About The Position

Tapestry is a team within Alphabet working to build the AI-powered electric grid. We are tackling one of the world’s most important infrastructure challenges: helping the energy system become more visible, understandable, reliable, affordable, abundant, and clean. Originally born at X, Alphabet’s moonshot factory, Tapestry brings together experts in energy, AI, software, engineering, and product to build tools that help the electricity ecosystem plan smarter, move faster, and operate more efficiently. This is a global effort. Tapestry supports partners across the U.S., U.K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy future. Joining Tapestry means doing high-impact work with a multidisciplinary team tackling a problem that matters at global scale. We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex challenges that face today’s electric grid. You will work closely with other Machine Learning Engineers, Data Scientists and Software Engineers across diverse ML domains spanning multimodal machine learning, information retrieval, natural language processing and agentic AI.

Requirements

• Master’s Degree/Bachelor's Degree in Machine Learning, Computer Science, Statistics or related field
• Experience in machine learning model development and engineering.
• Expertise in one or more of the following areas: multimodal machine learning NLP or agentic AI, planning, control and reinforcement learning
• Strong programming skills in Python and experience with ML frameworks like PyTorch or TensorFlow.
• Experience with building and deploying ML systems at scale, OR a proven ability to perform applied ML research and develop the state of the art in an academic setting

Nice To Haves

• 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.

Responsibilities

• Train, and deploy machine learning models in production environments.
• Work with senior team members to develop enterprise quality ML systems, spanning multiple ML domains
• Operationalize ML model training at serving at enterprise scale
• Stay abreast of the latest advancements in machine learning

Benefits

• Competitive salary and equity
• Medical, dental, and vision coverage
• Generous PTO and flexible hybrid work model
• 401(k) with employer contribution
• Professional development

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Associate degree