Senior ML Engineer, Energy Forecasting at Talcom

on-site · full time · Visa sponsorship

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Responsibilities:
- Design and implement production-grade forecasting models for renewable generation, consumption, and market signals.
- Build and maintain end-to-end ML pipelines: data ingestion (weather, market, telemetry), feature engineering, training, validation, and deployment.
- Deploy and operate models at scale using containerization and orchestration tools (Docker, Kubernetes) and cloud-native patterns.
- Validate data quality and model assumptions, run backtests and probabilistic evaluations, and quantify business impact of model improvements.
- Collaborate with trading, engineering, and ops teams to integrate forecasts into automated trading and optimization systems.
- Instrument monitoring, alerting, and retraining workflows to ensure reliability and continuous improvement.

Requirements:
- 5+ years in ML or data science with proven experience in time series and probabilistic forecasting.
- Strong Python skills and familiarity with ML frameworks (PyTorch, TensorFlow) and numerical libraries (NumPy).
- Hands-on experience deploying ML in production, including Docker, Kubernetes, and cloud-native data stores (Postgres, ClickHouse, Redis).
- Knowledge of spatio-temporal modeling, graph neural networks or transformers for time series is a plus.
- Experience with distributed processing, streaming systems, and MLOps best practices.
- Strong engineering mindset, ability to validate assumptions end-to-end, and clear communication with cross-functional teams.