Senior ML Engineer, Energy Forecasting at Talcom
May no longer be active — verify on the employer site
At a glance
- Company
- Talcom
- Location
- Netherlands
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 5–10 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this Talcom job
- 🏢 This is Talcom's only job here right now
- 🛂 Visa: Highly Skilled Migrant permit. 30 or older: €5,942 a month guide
- 💡 No salary shown. Ask Talcom if it is above the minimum.
Updated 2026-11-05, from our data and official sources.
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About the role
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.
Responsibilities
Design and deploy production-grade forecasting models for renewable energy production, consumption, and weather conditions. Build end-to-end ML pipelines and collaborate with stakeholders to shape the platform's machine learning architecture.
Requirements
Requires 5+ years of experience in Machine Learning or Data Science with deep expertise in time series forecasting and Python. Must have experience building production ML systems and data pipelines using Docker and Kubernetes.
Key skills
- Python — in 1200 other listings on The Stack
- Time Series Forecasting — not in any other listing on The Stack
- Machine Learning — in 291 other listings on The Stack
- PyTorch — in 92 other listings on The Stack
- TensorFlow — in 55 other listings on The Stack
- Docker — in 464 other listings on The Stack
- Kubernetes — in 585 other listings on The Stack
- Data Pipelines — in 113 other listings on The Stack
- Predictive Modeling
- MLOps
- Distributed Processing
- Spatio Temporal Modeling
- Probabilistic Forecasting
- Graph Neural Networks
- Transformers
- NumPy
On The Stack (as of 2026-11-05)
Frequently asked questions about Talcom
Is this Senior ML Engineer, Energy Forecasting role still open?
It was posted on 2026-06-08. Listings more than 30 days old may no longer be active, so check Talcom's site before applying.
Does Talcom offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Talcom's site.
Where is this role located?
The listing gives the location as Netherlands. It is marked on-site.
What skills does this role ask for?
The listing names: Python, Time Series Forecasting, Machine Learning, PyTorch, TensorFlow, Docker, Kubernetes, Data Pipelines, Predictive Modeling, MLOps, Distributed Processing, Spatio Temporal Modeling, Probabilistic Forecasting, Graph Neural Networks, Transformers, NumPy.