Machine Learning Operations Engineer
Machine Learning Operations Engineer
This job is no longer open
About Us
Leap’s mission is to combat climate change by enabling a reliable electric grid that runs on clean energy. The electric grid is transforming from dirty (but predictable) fossil fuels to clean (but less predictable) renewable energy. To do so, the grid needs more flexible demand and supply to help maintain stability and reliability.
Leap plays a crucial role in opening up wholesale energy markets to all distributed energy resources, enabling our partners to get paid for providing flexibility to the grid.
Leap is a privately-held tech company with funding from top VCs and well-known energy entrepreneurs. Our core operations are in the San Francisco Bay Area and Utrecht (NL), but we are a distributed workplace with teammates based in Atlanta, Boston, Boulder, Chicago, Maui, and Washington, DC.
Who are we looking for?
Do you get excited about automating machine learning models and optimizing operations? Are you interested in working with data scientists to build and deploy algorithms for stabilizing the electricity grid and contribute towards lowering the impact of electricity consumption on the environment?
You will be responsible for designing, implementing, and maintaining automated machine learning pipelines. This medior/senior position is essential for helping Leap to grow our business in existing and new markets. You will work with data scientists, engineers, and business stakeholders to ensure that machine learning models deliver the right predictions and insights in a timely, accurate and efficient manner. We take data seriously at Leap and you do too! In reality, this means constant collaboration with data scientists and data engineers in order to understand the data necessary for training and features, how the machine learning model works, and how to leverage existing data infrastructure. Of course, as a part of the team, you'll also talk to backend and front-end engineers to keep track of how our data and the associated insights are produced and consumed by our partners.
We focus on cross-collaboration in an agile work environment, so the ideal candidate would demonstrate technical depth and the ability to communicate complex technical concepts.
Here's what we hope you bring:
- Multiple years of experience designing and building machine learning pipelines
- Experience with features stores, experiment tracking & model monitoring
- Experience with Python and SQL
- You live in Europe in a timezone that is fully UTC, UTC+1, or UTC+2
- Experience with Spark / pySpark
- Experience with AWS
- Experience with Docker and Airflow
In this role you will:
- Design and build automated ML pipelines for a variety of energy related forecasting
- Transform various data sets for ingestion into the ML pipelines, such as meter data, wholesale electricity prices, and weather forecasts
- Collaborate closely with data scientists and the larger engineering team to build and maintain the ML pipelines
- Collaborate with business stakeholders for sharing the salient modeling results, and upgrade the automated delivery systems
What’s it like to work at Leap?
Product: At our core we are a tech company. We love technical challenges and build things that we are proud of and would like to use ourselves. Everyone is highly involved in building and designing our products, making them extremely valuable and a pleasure to use.
Purpose: Some of us worked in energy before, some of us haven’t. All of us would like to make a difference and do our part in helping the world move towards a more resilient grid run on renewable energy.
Fun: We work hard, but enjoy our time at work as well as outside of work. With the team spread out over multiple time zones we also embraced flexibility early on, and are focused on results instead of time spent in the office.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
This job is no longer open