Senior MLOps Engineer (part-time)

Impressit is looking for a Senior Data Scientist / ML Engineer (MLOps) to join a cross-functional product team building an intelligent asset orchestration platform for energy, mobility, and grid assets. This is a great opportunity to help launch a new Machine Learning practice from the ground up — building load-prediction models that will power real-world energy trading decisions — while working with modern cloud technologies and an international team.

— Assess historical asset/telemetry data to determine its quality, completeness, and suitability for building predictive models

— Design, build, and train machine learning models to predict available load/capacity across distributed assets

— Establish and own the full MLOps lifecycle: continuous training, testing, deployment, drift detection, retraining, and redeployment

— Set up and maintain an MLOps platform (Azure ML or Databricks)

— Expose trained models via endpoints/services consumable by other platform components

— Work closely with the wider engineering team while owning the ML workstream independently

— Proactively flag data gaps and technical risks

— 5+ years of commercial experience as a Data Scientist / ML Engineer, with strong, demonstrable MLOps expertise (this is the top priority for the role)

— Hands-on experience with time-series or telemetry-style historical data

— Proven ability to independently assess dataset quality, completeness, and suitability for modelling

— Solid experience with model deployment, versioning, and monitoring practices — comparable in spirit to CI/CD for traditional software

— Practical understanding of model drift detection, automated retraining, and redeployment

— Comfort working in notebook-based cloud ML environments (Azure ML and/or Databricks)

— Ability to work autonomously and get productive quickly, with minimal onboarding support

— Strong problem-solving skills and comfort working with ambiguous, real-world datasets

— Good communicator, comfortable working in cross-functional teams

— Upper-Intermediate or higher level of English

— Hands-on experience with Azure ML and/or Azure Databricks

— Strong data analyst skills: exploratory data analysis, data profiling, and data quality checks

— Experience in energy, grid, EV fleet, or IoT/telemetry domains

— Familiarity with Azure-native integration services (e.g., Event Hub, Service Bus)

— Exposure to grid trading, load forecasting, or energy market prediction use cases