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About Tapestry Tapestry is Alphabet’s moonshot for the electric grid, working at the frontier where energy’s complexity meets AI’s potential. We were born at X, the innovation lab responsible for breakthrough technologies like Waymo, Verily and Google Brain.
To keep pace with humanity’s growing energy needs, the world needs a grid that is visible and understandable. We provide that clarity by building advanced, AI-enabled analytical and planning tools that allow the entire energy ecosystem to plan smarter, move faster, and operate more efficiently—ensuring electricity remains reliable and affordable for everyone.
This is a global effort. Tapestry is proud to support partners in the U.S., U.K., Chile, New Zealand, Australia and Brazil as they build a cleaner, more resilient energy future. Joining Tapestry allows you to do the best work of your life as part of a multidisciplinary team of experts in AI, energy systems, software engineering and product design—all collaborating to reshape energy on a global scale. If you want to tackle problems that matter and build tools with real impact, we would love to meet you. Learn more about our team and our mission here.
About The Role
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.
How You Will Make 10x Impact
- 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
What You Should Have
- 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
It’d Be Great If You Also Had These
- Familiarity with MLOps practices and tools
- 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.
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.
