Our mission at Energetech is to accelerate the global path towards the green transition. We are an energy trading company that brings together the best talent from around the world to reinvent the way energy flows through global markets.
Who You Are
We are seeking an exceptional Machine Learning Engineer to join our dynamic team. As a Machine Learning Engineer, you will help develop innovative solutions and build robust strategies that create value and mitigate risk in the energy trading market. Our company is constantly challenging the norm and we are looking for a creative, talented individual who can help drive forward our mission of innovation.
- Collaborating with data scientists and business stakeholders to understand their needs and help them develop, test and deploy ML models
- Designing and implementing ML infrastructure and tools that support the end-to-end ML development lifecycle including model monitoring, serving and versioning
- Contribute to design, refinements, optimizations, and scalability for systems operating machine learning pipelines at scale
- Optimizing the performance of ML models in a production environment
- Developing and maintaining CI/CD pipelines for ML models and data
- Contribute to the MLOps culture and practices enabling the team to create solutions with less friction and solid security, and reliability.
- Work directly with the data scientists to enable successful deployments and maintainable production systems.
Skills & Qualifications
- Hands-on experience with ML frameworks, libraries, and deploying machine learning solutions using DevOps principles.
- Ability to build MLOps pipelines on cloud solutions (preferably in Azure).
- Experience with model registeries (such as MLFlow), workflow orchestration tools (such as
- Airflow, Dagster) and model serving tools (such as Seldon Core, FastAPI)
- CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, or similar tools.
- Experience with Docker and Kubernetes.
- Familiar with the unix shell, and shell scripting
- 3+ years of work experience with ML lifecycle management