Machine Learning Engineer, Tapestry

Machine Learning Engineer, Tapestry

Software Engineering

Location: Mountain View, CA

About the team:

Tapestry is X’s moonshot for the electric grid. We are a team of software engineers, power systems experts, and clean energy enthusiasts who are tackling climate change through our energy system. Tapestry's mission is to make the world’s electric grid visible so everyone can access clean, affordable, and reliable energy. We collaborate with partners globally to create AI-powered tools that help manage a carbon-free and secure electricity system.

Currently incubating at X, Alphabet’s innovation lab, we are building a team to scale Tapestry for global impact. We seek individuals passionate about revolutionizing the energy sector to join us at this critical growth stage.

About the role:

As an applied ML and data pipelines software engineer, you will own end-to-end development of breakthrough technologies that heavily rely on machine learning. You will collaborate with talented individuals on creative and ambitious efforts, working closely with software engineers, machine learning experts, domain experts, and product managers.

How you will make 10X Impact:

1. Explore, apply, and innovate state-of-the-art machine learning techniques to solve real-world problems on the electric grid.
2. Explore and de-risk novel technologies to extract data from unlikely sources.
3. Lead the design and implementation of ML data platforms and service frameworks.
4. Design and implement robust, automated, production-level software using horizontally scalable components.
5. Work effectively with cross-functional teams of engineers, product managers, and domain experts.
6. Provide direction and focus in areas of high ambiguity.

What you should have:

1. Bachelors/Masters in Computer Science or equivalent practical experience.
2. Experience applying machine learning for computer vision/image processing or time-series forecasting; will also consider DL experience with geospatial data, graph data.
3. 5-8 years of experience developing ML models, or a PhD in a relevant field with 2+ years of industry experience.
4. 3 years of experience with Python, Golang, or other equivalent languages.
5. Excellent written and verbal communication skills.
6. A passion for decarbonizing the electric grid.

It’d be great if you had these:

1. 2 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
2. Experience with building data pipelines (e.g., Beam, Dataflow, Flink, Hadoop, Spark).
3. Prior experience in ML modeling using TensorFlow, Pytorch, or Jax/Flax.
4. Consistent track record of delivering high-quality solutions to large, complex software problems.
5. Prior experience with setting the technical direction for small groups of engineers.
6. Experience working in start-up-like environments.

Compensation:

The US base salary range for this full-time position is $160,000 - $220,000 + bonuses + benefits. Our salary ranges are determined by role, level, and location. 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 reflect the base salary only, and do not include bonuses or benefits.

Diversity and Inclusion:

At X, we celebrate and thrive on difference for the benefit of our employees, products, and community. We are proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

If you have a disability or special need that requires accommodation, please contact us at: x-accommodation-request@x.team.

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