Senior Machine Learning Research Engineer (m/f/d)

Terra One Climate Solutions GmbH; Berlin; Vor Ort; Vertraulich; Vollzeit

Zusammenfassung

Join a leading company in renewable energy as a Senior Machine Learning Research Engineer. Contribute to our innovative battery storage solutions and AI-based energy trading, working on machine learning pipelines to improve real-time price predictions. Bring your expertise in ML and teamwork to drive our mission for climate neutrality.

Qualifikationen

• 2+ years of industry experience in machine learning.
• Proven experience building and deploying ML models in production.
• Strong foundation in machine learning and sequence models.

Aufgaben

• Improve aspects of current machine learning pipeline for intraday price predictions.
• Implement and experiment with new ideas to improve prediction accuracy for intraday prices.
• Work closely with data engineers and ML experts to innovate across the value chain.

Kenntnisse

Machine Learning

Deep Learning

Python

Empirical Experimentation

Team Communication

High Intellectual Curiosity

Ausbildung

University degree in computer science, mathematics, physics or related field

Tools

ML frameworks (PyTorch preferred)

Distributed Computing

Jobbeschreibung

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Senior Machine Learning Research Engineer (m/f/d), Berlin

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Client:

Terra One Climate Solutions GmbH

Location:

Berlin, Germany

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

04d816dbbb8a

Job Views:

2

Posted:

21.06.2025

Expiry Date:

05.08.2025

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Job Description:

About Us:

Welcome to Terra One – an exciting-fast growing company focused on developing and operating large-scale battery storage systems in Germany. With a focus on innovation and sustainability, our company is driving forward the expansion of renewable energy infrastructure in order to make a significant contribution to achieving climate neutrality.

Our Mission:

At Terra One, we accelerate the expansion of renewable energy infrastructure by developing and implementing innovative solutions. Our initial focus is on battery storage, a crucial component for establishing a flexible and environmentally friendly power grid. By providing energy when it is most needed, we help improve the reliability and efficiency of the power grid while simultaneously reducing CO2 emissions. Equally important to our mission is our AI-based energy trading in the European market, which works hand in hand with our battery storage solutions.

Our Team:

The energy trading unit is responsible for optimizing assets across all markets, balancing renewables, and proprietary trading. We trade short term power algorithmically in an expanding geographical scope and have a highly technical team of veteran software engineers, leading AI experts and power trading professionals.

In order to reach our goals and increase our impact we are looking for talented people to join our team who want to contribute their knowledge and passion to the energy transition. We are looking to strengthen our team with one additional Senior Machine Learning Research Engineer (m/f/d) role. In this role, you will work on all aspects of our cutting-edge machine learning pipeline for intraday price predictions (dataset creation, model training, model evaluation, model deployment). This senior position requires a minimum of 2 years experience within the deep learning field.

If you’re ready to join our team and make an impact in the energy transition, we would be happy to receive your application. We look forward to hearing from you and shaping the future of energy together!

Your Tasks:

• Improve all aspects of our current machine learning pipeline for intraday price predictions: dataset creation, dataset loading, model training, model evaluation, and model deployment
• Improve and create tooling and infrastructure to make the above super easy and fast (for example, tooling to provision GPU machines or tooling to evaluate models across many different benchmarks quickly)
• Further scale and improve our production pipeline that runs our models to produce price predictions in real time
• Implement and experiment with new ideas to improve prediction accuracy for intraday prices (for example new input features, improvements to the model architecture, expanding models to more countries, or scaling up the model)
• Work closely with our data engineers, traders, and ML experts to come up with novel ideas across our whole value chain
• Work closely with our software and backend engineers to ensure reliable and performant production operations

What we expect from you:

• You’re excited about driving progress in a fast-moving startup company
• Strong and respectful communicator with ability to work in a team
• High intellectual curiosity and grit combined with a commercial mindset
• High level of integrity, ethical standard and good judgment
• You can be inquisitive and rigorous but also pragmatic
• You are comfortable with empirical experimentation to produce actionable insights
• Fluent in English, German is a plus

Qualifications:

• University degree in computer science, mathematics, physics, or related field
• Strong Python programming skills and experience with ML frameworks (PyTorch preferred)
• Proven experience building and deploying ML models in production
• 2+ years of industry experience in ML
• Strong foundation in machine learning, particularly deep learning and sequence models
• Experience with distributed computing and handling large-scale data
• Prior experience with time series forecasting and knowledge of energy markets are a plus

Application Requirements:

• Motivation Letter: A brief letter outlining why you are interested in this role and how your background aligns with our mission.

• Technical Summary: Within the motivation letter, please include a short explanation of a technical project or piece of work you have contributed to that showcases your expertise.

• Technical Work Samples: If possible, share any examples of your technical work—this could be a link to your GitHub profile or another relevant portfolio. Text-based summaries are also welcome if public sharing is not possible.