Senior MLOps Engineer (m/w/d)
Core
Act as the technical bridge between data science and software engineering to build reliable, maintainable production ML systems for forecasting and trading models.
Role type
Senior MLOps Engineer
Builds
Data and feature pipelines, deployment/orchestration platforms, and monitoring systems for batch and real-time ML workloads
Domain
Financial technology / Energy markets / Real-time trading
Deliverable
production ML models
Required skills
Python, software engineering best practices (CI/CD, testing, modular design), MLOps practices (pipeline setup, deployment, monitoring), ML/statistical modeling collaboration, independent problem-solving
Preferred skills
Energy/power markets domain experience, orchestration tools (Airflow), MLOps toolchains (MLflow, Sagemaker), streaming systems (Kafka), large-scale data tooling (Spark, Dask), AWS cloud experience
Responsibilities
Design and build data/feature pipelines at scale; leverage deployment platforms for batch and real-time workloads; establish monitoring for model drift, data quality, and latency; partner with data scientists on model design and validation; champion engineering rigor and ML best practices; contribute to technical roadmap; guide junior colleagues through design and code reviews
Seniority
Senior, hands-on IC with mentorship responsibilities