Job Title: ML/Data Engineer

Application Deadline: 23 December 2024

Target start date: 6 January 2025

Location: Fully Remote (open globally)

Company Overview:
Open Energy Transition is a non-profit organization dedicated to accelerating the global energy transition through innovative open-source energy planning solutions. We are a team of passionate individuals committed to creating a sustainable future by enabling accessible, effective, and transparent energy management tools. More info at our website.

Position Overview:
We are seeking a highly motivated ML/Data Engineer to join our team and drive the development and implementation of cutting-edge machine learning and data engineering solutions. You will play a key role in designing and maintaining scalable data pipelines, creating robust ML models, and integrating solutions into our open-source energy planning tools. Since most of OET’s modellers work with the PyPSA model, written in Python and run using Snakemake, knowledge of these or the ability to learn quickly is required. The engineer would also need to create or work with CI/CD pipelines to ensure code quality and automate testing and deployment.

The ideal candidate is a problem-solver with a deep understanding of data and machine learning systems, and a passion for advancing renewable energy solutions. As we are a fully-remote young organization, an ideal candidate must also be an excellent communicator, able to collaborate asynchronously (e.g., Discord, Google Docs) and work independently, and keen to learn new skills and be flexible with tasks as needs arise.

Key Responsibilities:

• Data Pipeline Development: Design, build, and maintain scalable and efficient data pipelines to collect, process, and transform large datasets for analysis and modeling.
• Machine Learning Integration: Develop, train, and optimize machine learning models to support energy planning, forecasting, and decision-making processes.
• Collaboration: Work closely with cross-functional teams, including software developers, data scientists, and domain experts, to understand requirements and deliver integrated solutions.
• Open-Source Contributions: Ensure all development aligns with open-source principles, contributing to public repositories and engaging with the broader open-source community.
• Performance Optimization: Continuously improve the performance, reliability, and scalability of data systems and machine learning workflows.
• Documentation: Write clear, concise, and comprehensive documentation for data pipelines, machine learning models, and deployment processes.
• Quality Assurance: Implement testing and monitoring frameworks to ensure data quality and model accuracy.

Required Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• Experience: 3+ years of experience in ML engineering, data engineering, or a related role.
• Technical Skills:
• Proficiency in programming languages such as Python or Java.
• Hands-on experience with data processing frameworks (e.g., Apache Spark, Hadoop).
• Expertise in ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn), and experience using ML for time-series prediction is a plus.
• Experience with CI/CD (e.g., GitHub Actions, GitLab, Jenkins), cloud platforms (e.g., AWS, GCP, Azure) and containerization tools (e.g., Docker, Kubernetes).
• Strong knowledge of SQL and NoSQL databases.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Problem-Solving Skills: Ability to translate complex problems into actionable solutions.
• General:  Effective asynchronous communication skills, ability to work independently, and a growth mindset is a must!

Preferred Qualifications:

• Experience with energy modeling, renewable energy systems, or sustainability-focused projects.
• Familiarity with open-source software development and contributions.
• Knowledge of version control systems (e.g., Git).

What We Offer:

• A mission-driven, collaborative, and flexible work environment.
• The opportunity to work on impactful projects that advance the global energy transition.
• Professional development opportunities, including conferences and training programs.
• Competitive salary and benefits package.