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Machine Learning Engineer, Intern

Powertown
Posted 3 days ago, valid for 23 days
Location

Boston, Suffolk, MA

Salary

$50 - $60 per hour

Contract type

Full Time

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Sonic Summary

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  • The position involves building intelligence around peak shaving, load behavior, utility signals, and storage opportunities.
  • Candidates should have a strong background in fields like Computer Science, AI, or Electrical Engineering and possess at least 3 years of relevant experience.
  • The ideal candidate is a proactive technical thinker who leverages machine learning and other tools without being overly reliant on AI.
  • Experience in energy storage, utility data analysis, and optimization techniques is highly preferred, along with evidence of exceptional ability through personal projects or research.
  • The salary for this role is competitive and commensurate with experience, reflecting the high-stakes nature of the work in the energy sector.

What you'll do

  • Build intelligence around peak shaving, load behavior, utility signals, and storage opportunities

  • Create agents that research, extract, compare, reason, and propose next steps

  • Turn grid data into decision systems

  • Use AI aggressively, then audit it ruthlessly

  • Invent workflows the industry does not yet have

Preferred majors

Computer Science, Artificial Intelligence, Machine Learning, Data Science, Applied Math, Statistics, Electrical Engineering, Energy Systems, Operations Research, Power Systems, Physics, or another rigorous quantitative field.

Ideal candidate

  • You are a superstar technical thinker who uses ML as one of many tools

  • You have very high agency. You do not wait for a clean dataset, a polished problem statement, or a perfect roadmap. You form hypotheses, build instruments, test ideas, and keep moving

  • You are AI-first but not AI-reliant. You use agents, LLMs, automation, and modern tools to move faster, but your own judgment stays in charge

  • You are drawn to the grid because it is physical, messy, high-stakes, and full of hidden leverage

Preferred qualifications

  • Evidence of exceptional ability: original research, serious side projects, open-source work, startup building, competitions, technical writing, or shipped systems

  • Experience with energy storage, utility data, tariffs, load analysis, peak shaving, grid infrastructure, electricity markets, forecasting, optimization, anomaly detection, agentic workflows, or AI-assisted research systems

  • Exceptional ability exemplified through personal projects

 



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