Machine Learning Engineer

About Storio

Storio Energy offers energy storage solutions to businesses in France around 2 use cases :

Solar panels + battery : the battery boosts the self-consumption rate, providing greater autonomy and resilience.

Standalone battery for electro-intensive clients : the battery charges when electricity prices are low to make its energy available when prices are high, enabling ~20% savings.

We want to enable a world 100% powered by low-carbon energy at an affordable price. We do this by helping our clients come out as winners of the ongoing energy transition. This also means improving the competitiveness and resilience of industrials companies and pushing them towards a greater electrification and decarbonization of their activity.

Our energy management software controls batteries in real-time to maximize the savings on our customer’s bills and to generate additional revenues by stabilizing the electric grid. Providing ancillary services using batteries that are installed on customer sites is new in France and definitely hard to do : we’re the pioneers of B2B energy storage in France and many challenges lie ahead of us!

We provide a turnkey service, working with our clients from initial feasibility studies, to purchasing the batteries, installing them on site, and operating them seamlessly using our software platform during the 15+ years of operations.

Storio raised a 5M€ seed round from Lowercarbon Capital (#1 climate tech fund globally) and Bpifrance. Our team gathers experts from EDF Renewables, NW Group, Agregio, repeat entrepreneurs from the AI space, and experienced software engineers.

The opportunity

We’re a growing team of around a dozen, and we’re looking for a Machine Learning Engineer to design and build the forecasting engine at the heart of Storio’s real-time control system for energy storage assets.

Our batteries tap into multiple revenue streams: spot and day-ahead arbitrage, ancillary services (aFRR), demand response programs (AOFD, NEBEF), solar self-consumption optimization, and more. Arbitraging between these mechanisms requires highly accurate forecasts of the energy consumption and solar production of the industrial sites where our assets operate. A poor forecast can mean a missed opportunity —or worse, a costly penalty.

This role offers a unique opportunity to grow in a fast-paced, hands-on environment, working alongside experienced engineers and entrepreneurs. We foster a culture of curiosity and knowledge-sharing, where everyone learns from one another and moves fast to turn ideas into impact.

Responsibilities

Lead the development of forecasting models for consumption, solar production, energy prices, and other key signals that drive the operation of Storio’s storage assets.

Own the deployment, orchestration, and monitoring of forecasting solutions to ensure reliability and scalability in production.

Stay at the forefront of the field, continuously evaluating new methods and technologies to keep Storio’s forecasting capabilities both cutting-edge and pragmatic.

Collaborate across the engineering team, contributing to broader software and data engineering efforts that support our end-to-end system.

Requirements

2+ years of work experience, which includes some software development within a team environment.

Proven experience building ML pipelines, from modeling down to implementation and orchestration.

A BS/MS/PhD in a scientific field or equivalent experience.

This position is based in Paris.

We know that great candidates don’t always meet every requirement. If you’re enthusiastic about the role, please apply!

Bonus points

Expertise in ML applied to forecasting.

Familiarity with or past experience in the energy sector.

How to apply : reach out to jobs@storioenergy.com

Perks

A competitive salary and equity package.

Nice office in Paris 10th arrondissement + flexible remote work policies.

10€ meal voucher per working day

30€/month if you commute by bike (”forfait mobilité durable”).

Company retreat 2x/year with the whole team.

Standup meetings where people actually stand up

ALT