About this opportunity
Tapestryenergy lists this Machine Learning Engineer opportunity in mountain view, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
About Tapestry
Tapestry is a group within Google 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 products 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. 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
3+ years of 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
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.
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Worksite address
mountain view, CA, 94039, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.