Senior MLOps Engineer

About the role

The Senior MLOps Engineer will act as a technical bridge between data science and software engineering to transform research models into reliable production systems. This role involves designing data pipelines, managing model deployment, and establishing observability for forecasting and trading models. You will work within a cross-functional team to ensure scalability and maintainability while championing engineering best practices.

Responsibilities

• Act as the technical bridge between data science and software engineering to build reliable, maintainable production systems.
• Design and build data and feature pipelines for forecasting and trading models at scale.
• Leverage deployment, orchestration, and serving platforms to bring models into production for batch and real-time workloads.
• Establish monitoring and observability for models in production, including drift, data quality, latency, and failure modes.
• Partner with data scientists on model design and validation with a focus on scalability and production risk.
• Champion engineering rigor and ML best practices to foster a data-driven engineering culture.
• Contribute to the technical roadmap and mentor junior colleagues through design and code reviews.

Required skills

• MLOps
• Python
• Data pipelines
• Model deployment
• Monitoring
• CI/CD
• Statistical modeling

Nice to have

• Energy sector
• Airflow
• MLflow
• Sagemaker
• Kafka
• Spark
• Dask
• AWS

Qualifications

• University degree in an engineering or analytical field (Computer Science, Mathematics, Physics, Statistics, Engineering or a related discipline)
• 5+ years of engineering experience with ML systems in production

Benefits

• Virtual share options
• Annual professional development budget
• Health and sport subsidy
• Public transportation subsidy
• Lunch/dinner allowance vouchers
• MacBook or Windows laptop
• iPhone
• Ergonomic workplace setup
• AI developer tools access
• Regular team events

About the Company

Flexa is an energy technology company that dispatches energy from customer fleets in real time against energy markets. The company focuses on solving complex distributed decision-making problems where infrastructure performance directly impacts customer financial outcomes.