Machine Learning Engineer Time Series

Machine Learning Engineer Time Series

At Sybilion, we are building the decision layer for industrial markets. Industrial companies operate in environments shaped by thousands of external signals: commodity prices, trade flows, energy markets, weather, geopolitics, logistics constraints, and shifting demand. Most decisions today are still made using spreadsheets and intuition. Sybilion changes that. Our platform discovers the signals that truly matter across billions of time-series data points and turns them into decision-ready intelligence. Procurement teams decide when to buy. Commercial teams decide how to price. Supply chains decide how to position inventory. We are not building dashboards. We are building the world model industrial companies use to make decisions under uncertainty. To do this, we are looking for outlier ML engineers who want to work on one of the hardest problems in applied machine learning: understanding complex real-world systems through time-series modelling.

The Role

You will work directly on the core modelling systems behind Sybilion’s decision layer. This means building models that discover relationships across massive time-series datasets and turn them into reliable forecasts, causal insights, and decision signals. You will work closely with the founders and product team in a high-ownership, high-impact environment.

What You’ll Work On

Time-Series Modelling at Scale

Build models that understand and forecast complex market systems. Examples include: Commodity and chemical price dynamics, Supply-chain demand signals, Trade flow shifts and macro indicators, Energy and logistics cost dynamics, Production and consumption cycles. You will design and evaluate models such as: classical forecasting models (ARIMA, ETS, state-space), modern ML models for time-series prediction, multivariate signal discovery models, regime detection and structural break modelling, probabilistic forecasting and uncertainty estimation.

Signal Discovery

One of Sybilion’s core problems is discovering which signals actually matter. You will work on systems that: search large time-series spaces for predictive relationships, identify causal drivers, detect regime changes and structural breaks, filter noise from true market signals.

Decision-Grade Forecasting

Our models do not exist for research papers — they exist to drive real decisions. You will help translate models into: decision thresholds, uncertainty ranges, scenario simulations, early warning signals. Your work will influence millions of euros in procurement and pricing decisions.

Production Systems

You will help turn modelling approaches into robust production pipelines, including: feature pipelines for large time-series datasets, scalable modelling workflows, evaluation and backtesting frameworks, automated model monitoring.

Who We’re Looking For

We are looking for outliers. People who move faster, think deeper, and build better systems than the average engineer. You may recognise yourself if you: obsess over understanding real systems, enjoy modelling messy real-world data, care about correctness and robustness, like solving problems that are not well defined.

Must Have

• Strong Python (NumPy, pandas, PyTorch/JAX/Scikit-learn or similar)
• Experience building time-series models
• Deep curiosity about real-world systems
• Ability to design rigorous evaluation and backtesting frameworks
• Comfort working with large datasets and imperfect data
• Strong problem-solving ability

Strongly Valued

• Experience with forecasting methods (ARIMA, ETS, Prophet, state-space models)
• Multivariate or causal modelling
• Probabilistic forecasting
• Experience with large-scale time-series datasets
• SQL / data pipelines / cloud environments
• Experience in commodities, macroeconomics, or supply chains

What Success Looks Like (First 6 Months)

• You build models that materially improve forecasting accuracy in at least one market domain.
• You understand and advise customers.
• You contribute to Sybilion’s signal discovery engine.
• You design robust evaluation and backtesting systems.
• Your models are used by customers in real decision workflows.

Why Join Sybilion

We are building a company at the intersection of: machine learning, economics, complex systems, industrial decision-making. This is not a typical SaaS product. It is an attempt to build the decision infrastructure for real-world markets. If that excites you, we would love to talk.

Key skills/competency

• Machine Learning
• Time Series Analysis
• Python
• Forecasting
• Signal Discovery
• Data Modeling
• Causal Inference
• Probabilistic Modeling
• Production Systems
• SQL