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Machine Learning Engineer

Develop cutting-edge deep learning models to optimize the electricity grid for decarbonization
San Francisco Bay Area
Mid-Level
$160,000 – 205,000 USD / year
yesterday

Machine Learning Engineer

Gridmatic Inc. is a high-growth startup with offices in the Bay Area and Houston that is accelerating the clean energy transition by applying our expertise in data, machine learning, and energy to power markets. We are the rare startup that has multiple years of profitability without raising venture capital. Gridmatic is a great place to work with a culture that values teamwork, continuous learning, diversity, and inclusion. We move quickly and fix things. We are environmentally and data-driven, with a growth-oriented, academic mindset. We value integrity as much as excellence.

We are looking for a Machine Learning (ML) Engineer to develop deep learning forecasting models to help quickly decarbonize the electricity system. This is the ideal role for someone who wants to use their programming skills in a fast-paced environment, enjoys learning every day, and enjoys bouncing ideas off coworkers and collaborating on tough problems. This is a role where you will see your ideas tested and quickly proven in real-world settings, and where you will be on the forefront of cutting-edge technology in a nascent space.

Responsibilities

  • Design state-of-the-art machine learning models for the electricity grid.
  • Research and implement ML algorithms and tools for generative time-series forecasting.
  • Extend existing ML libraries and frameworks.
  • Run tests and experiments to rapidly iterate and improve production models.
  • Monitor and maintain the quality of existing models.
  • Put creative approaches to the test with fast, revenue-impacting results.

Requirements

  • Proven experience as a Machine Learning Engineer or similar roles, such as internships or research experience.
  • Understanding of data structures, data modeling and software architecture.
  • Deep knowledge of math, probability, statistics and algorithms.
  • Fluency in Python and machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn, numpy, and pandas).
  • Excellent skills in communication and teamwork.
  • Outstanding analytical and problem-solving skills.
  • BSc in Computer Science, Computer Engineering, Electrical Engineering, Mathematics or similar field; MS or PhD is a plus.

$160,000 - $205,000 a year Not including Options

Taking care of you today:

  • Continuing Education Opportunities
  • Flexible PTO
  • Medical, Dental and Vision plans with competitive employer contributions
  • Pre-Tax commuter benefits
  • $1500/year non profit donation matching program through Millie
  • Home Office Stipend
  • Protecting your future for you and your family:

    • 401K contribution match up to 4%
    • Company-paid parental leave
    • Company Paid Life Insurance

    FAQ

    What's your policy on remote work? We value the ability to work and collaborate in-person in our early stage as a startup, so Gridmatic has a hybrid policy of "50% in-office". Most of the company works in our Cupertino office 2 or 3 days a week.

    How does the interview process work? We start with 1-2 initial conversations about the role, your past experience, and Gridmatic as a company. We then have a skills assessment which involves a take-home project; if that goes well, you'd come onsite to Cupertino to talk to the team.

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Machine Learning Engineer
San Francisco Bay Area
$160,000 – 205,000 USD / year
Engineering
About Gridmatic