Machine Learning Engineer, Intern

Powertown; Boston (MA); On-site; USD 140,000 - 190,000; Full time

Job summary

Powertown is seeking a highly autonomous, AI-first researcher in Boston to turn grid data into decision systems. You’ll build intelligence around peak shaving, storage opportunities, and utility signals, and craft agents that research, extract, compare, reason, and propose next steps.

You are drawn to the grid because it is physical, messy, high-stakes, and full of hidden leverage, and you’ll push boundaries with experiments and instrumentation.

Qualifications

• Evidence of exceptional ability: original research, 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.

Responsibilities

• 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

Education

Computer Science or related quantitative field (Preferred majors)

Artificial Intelligence / Machine Learning

Data Science / Statistics

Job description

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