ML Research Scientist

About Parisi Labs

Parisi Labs is an AI company building learning systems for complex physical environments. We combine historical and live data with real operational context to help people understand the present, evaluate possible futures, and make better decisions.

Energy is our first proving ground. Ask The Grid (https://askthegrid.com) is our public product for exploring the systems, markets, and assets that make up the power grid. We are a small technical team working across machine learning, data infrastructure, software, and real-world operations.

About The Role

We are looking for an ML Research Scientist to develop, implement, and test our core models with our co-founder and Chief Scientist, Matt Miller. Matt's background spans MIT Media Lab, Bluefin Labs, nearly a decade in Twitter Cortex Applied Research, and leading Data and ML at Automattic.

You will contribute original research and own independent research directions while supporting the team's core model development. We are looking for someone who combines invention with careful experimentation, strong engineering, and a commitment to making research useful in the real world.

Our current work centers on generalizable time-series foundation models across electricity prices, demand, and generation on multiple grids. These systems reflect interactions among human behavior, energy markets, weather, and the physical grid. Open research questions include generalization, physical constraints and interactions, multimodal and event data, world modeling, and simulation.

What You Will Own

• Collaborate with the Chief Scientist to develop original advances in time-series foundation models and world models.
• Train and evaluate models on difficult, valuable forecasting tasks grounded in real operational data.
• Own research directions from hypothesis through implementation, experiments, ablations, and clear technical conclusions.
• Explore how multimodal inputs, event data, and physical constraints can improve model behavior and generalization.
• Work with engineers to translate successful research into reliable systems that support real decisions.
• Explore how advances can extend beyond energy into supply chain, logistics, water, oil and gas, manufacturing, and predictive maintenance.
• Build reproducible research practices and communicate what changed, what the evidence shows, and what to investigate next.

First 90 Days

• 30 days: Reproduce the current model and evaluation system, understand its strengths and limitations, and identify a focused research opportunity with the Chief Scientist.
• 60 days: Own an experiment from hypothesis through implementation, evaluation, and failure analysis, with reproducible results and a clear readout.
• 90 days: Establish an independent research direction, deliver evidence-backed findings, and work with engineers to translate promising results into the core system.

Why Parisi Labs

Research is central to what we build. You will help shape an early company's research agenda, develop original intellectual property, and test ideas against difficult problems in physical industry. You will work directly with the founders and engineers who turn those advances into useful products.

You May Be A Fit If

• You have five or more years of combined postgraduate and industry experience in machine-learning research.
• You have a demonstrable record of original research contributions that advance the field or deliver meaningful business impact.
• You bring deep expertise in relevant areas such as time-series foundation models, world modeling, simulation, dynamical systems, or optimization.
• You have strong coding and engineering skills and can build and test the ideas you develop.
• You understand experimental design and can distinguish real improvements from noise, data problems, and evaluation artifacts.
• You are creative, adaptable, and comfortable owning an independent research direction while collaborating on the team's central priorities.
• You communicate technical conclusions clearly and care about translating research into practical impact.

We are looking for PhD-level depth, but recognize that expertise can be developed in many ways. A particular credential is not required; evidence of research judgment, invention, and the ability to execute matters more.

Helpful Background

• Research or applied experience in energy, supply chain, manufacturing, or other complex physical systems.
• Experience with multimodal or event data, physical constraints, and generalization across domains.
• Experience working with engineers to bring research into production under practical data, compute, or deployment constraints.

Location And Working Style

Boston/Cambridge is strongly preferred. New York City can work for an exceptional candidate with a regular in-person cadence.

Compensation And Benefits

Base salary range: $210K-$275K, plus meaningful early-stage equity, medical, and dental benefits. Final compensation depends on level, location, experience, and role scope.

Interview Process

1. Conversation with the Chief Scientist.
2. Research working session or compact experiment and evaluation review.
3. Technical calibration with the CTO.
4. In-person final in Boston/Cambridge or New York City.
5. Offer review.