Senior Research Engineer - Machine Learning

About the team:

Tapestry is X’s moonshot for the electric grid. We’re transforming how the world makes, moves and uses electricity, using AI to reshape energy on a global scale.

We’re looking for curious minds who want to be a part of this extraordinary moment in energy. You would be joining a multidisciplinary team from a wide variety of experiences and backgrounds—from ML/AI and power systems experts to software engineers and energy entrepreneurs– working together to realize Tapestry’s mission to make the grid visible so that everyone, everywhere can access reliable, abundant, and clean energy.

Tapestry is incubating at X, Alphabet’s Moonshot Factory—the birthplace of breakthrough technologies like Waymo, Android and Google Brain. At Tapestry, you’ll have the chance to be part of a rapidly growing team that has the agility and impact of an early stage company with the resources and technical excellence of Alphabet. If developing multimodal AI solutions gets you up in the morning and load growth challenges keep you up at night, we'd love to meet you.

Learn more about our team and our mission here.

About the role:

We're looking for a Senior Research Engineer to join the Machine Learning team. In this role, you will be responsible for developing and deploying state of the art machine learning models to solve complex challenges that face today’s electric grid. You’ll have the opportunity to lead model building and development across diverse ML domains such as computer vision, natural language understanding, representation learning and agentic AI. In this role, you will be responsible for end to end ML model training and deployment, working with  and mentoring junior machine learning engineers, helping  lead cross-functional collaborations and build the state of the art machine learning models to help power the grid of tomorrow. 

How you will make 10x impact:

• Design, train, and deploy machine learning models in production environments.
• Lead the end to end development of ML systems for  one or more of multimodal machine learning, agentic systems and LLMs, representation learning
• Actively collaborate with leaders in  product, engineering, and data science teams to address key business problems
• Mentor junior engineers and scientists and contribute to the team’s technical growth.
• Stay abreast of the latest advancements in machine learning

What you should have:

• Master’s Degree/Bachelor's Degree in Machine Learning, Computer Science,  Statistics or equivalent practical experience.
• 6+ years of professional experience in machine learning model development and  engineering.
• Strong programming skills in Python and experience with ML frameworks like PyTorch or TensorFlow.
• Experience with building and deploying ML systems at scale, and a proven ability to perform  applied ML research and develop the state of the art
• Proven ability to work on cross-functional projects and deliver results in a fast-paced, collaborative environment

It’d be great if you also had these:

• PhD in Machine Learning, Computer Science, Statistics, or a related field
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Familiarity with MLOps practices and tools.
• A strong portfolio of projects demonstrating expertise in multiple ML domai

Our values

• Take charge: We take initiative and own outcomes that move the mission forward.
• Transform with purpose: We build solutions that solve real problems and create meaningful impact.
• Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
• Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
• Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.

What we offer

A culture that supports growth, ownership, and meaningful impact, along with:

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

The US base salary range for this full-time position is $166,000 - $244,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.

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