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
- 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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Skills Required
- Master's or 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 areas: multimodal machine learning, NLP, agentic AI, planning, control, or reinforcement learning.
- Strong programming skills in Python.
- Experience with ML frameworks such as PyTorch or TensorFlow.
- Experience building and deploying ML systems at scale, OR demonstrated ability to perform applied ML research and develop state-of-the-art methods.
- PhD in Machine Learning, Computer Science, Statistics, or related field.
- Experience with cloud platforms (AWS, GCP, or Azure).
- A strong portfolio of projects demonstrating ML expertise.
X, The Moonshot Factory Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about X, The Moonshot Factory and has not been reviewed or approved by X, The Moonshot Factory.
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Fair & Transparent Compensation — Pay is considered competitive for core technical and senior roles, with employer-posted ranges and clear statements that total compensation includes base, bonus, equity, and benefits. Feedback suggests posted bands and explicit structure provide clarity on how pay is constructed.
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Parental & Family Support — Family support is described as generous, including paid parental leave, baby bonding, and transitional support for parents returning to work. Fertility treatments and maternity care are also covered, indicating depth in family-focused provisions.
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Retirement Support — Retirement programs include a 401(k) with a notable company match and immediate vesting of matched funds. Additional financial supports such as student loan reimbursement and coaching strengthen long-term financial security.
X, The Moonshot Factory Insights
What We Do
We create breakthrough technologies to help solve some of the world’s biggest problems. Born at Google, we got our start creating self-driving cars and smart glasses. Since then, we’ve continued to bring sci-fi ideas into reality.
