Volatile energy prices, intermittent renewable production, electrification of heat and transport, explosion of data sources; the electricity grid is changing at high speed towards a future less reliant on fossil fuels.
Are you up for this transformation?
About us Augmented Energy is on the mission to offer turn-key solutions to energy players, enabling them to transition towards a decarbonised electricity mix and ultimately offer greener energy services.
We are developing software solutions to integrate and manage all types of intermittent and flexible assets within our customer's existing operations (onsite renewable generation, behind-the-meter batteries, charging stations), to improve their electricity carbon footprint as well as their revenues.
We are a young company with a team of experienced founders and we are growing strongly; we have landed several contracts at the forefront of energy innovation in France.
We are looking for talents to tackle the challenges of today's energy transition!
About the rôle : As we experience an increased demand for our energy management solutions, our team is entering into the next stage of our growth, scaling up our operations to thousands of concurrent processing tasks across grid data, market data, consumption and production data.
We are looking for a MLOps Engineer to help us optimize and expand our ML pipelines, infrastructure and deployment capabilities.
Tasks You will be amongst our first employees and shape the company and its vision from the ground up.
As a MLOps Engineer, you will be instrumental in optimizing and expanding our ML pipelines, infrastructure and deployment capabilities.
Working closely with the Head of ML, a Data Scientist and the Tech Team, you will primarily: Design, develop and deploy ML pipelines for training & inference of timeseries forecasting models (data loading, data validation, feature engineering, modeling, serialization) Automate and monitor the deployment, retraining, and performance of ML models in production (Argo) Improve and manage our ML software ecosystem (keras 3 with the tensorflow backend, scikit-learn, pandas/polars, jupyterhub/jupyterlab, custom framework for ML pipelines & registry) and our cloud-based ML infrastructure (AWS, IaC via Terraform, K8s cluster with GPU nodes) Collaborate with domain experts to ideate and research new scientific and engineering approaches to improve model performance both technically and functionally.
Depending on your experiences and interests, the position could also encompass DevOps and Data Engineering activities, as well as more research-driven Data Science activities.
Requirements About you We're looking for a purpose-driven and empathetic MLOps engineer who is comfortable with autonomy and solving complex problems that will enable us to forecast and optimize thousands of distributed assets: Passion for clean energy and fighting climate change 5+ years in Software / MLOps engineering, preferably in a data-intensive environment.
Comfortable writing production-ready code in python, integrating models and running ML pipelines into a cloud-based infrastructure An appreciation for the scientific method as applied to the commercial world; a talent for converting business problems into a mathematical framework; resourcefulness in overcoming difficulties through creativity and commitment; a rigorous mindset in evaluating the performance and impact of models upon deployment Collaboration-first mentality, with a willingness to teach as well as learn from others Ability to proactively learn and adapt to new tools, technologies, and systems.
We mostly care about your ability to deliver great work, so we do not expect you to be an expert in the specific technologies we use, though we're enthusiastic Pythonistas!
More about our tech: https://github.com/noosenergy / Benefits Fully remote (within 2h time difference of CET) French CDI or exclusive service contract elsewhere Good pay and flexibility Applications will be reviewed on a rolling basis.
We can't wait to hear from you!
You are joining an entrepreneurial adventure with a flat structure, real autonomy and project ownership as well as the ability to further build your team in the future.
We believe in a fully remote company and we currently have people in 6 different countries.
You are expected to help define the workstyle and lifestyle of the company.
We do not discriminate and will consider absolutely anyone as long as you have the right skills, drive and attitude.