Founding Machine Learning Engineer
Hybrid (Paris, France)€80/hr - €130/hrFull-timePosted 11mo ago
About the role
We are seeking a Founding Machine Learning Engineer to architect, train, and deploy large time-series foundation models, working closely with founders to push state-of-the-art in forecasting across multimodal data. The role involves building production-ready models, conducting reproducible experiments, and mentoring future team members in a fast-growing startup.
Responsibilities
- Architect and train time-series foundation models using diverse datasets, integrating multimodal inputs like numerical time series, text, location and image data
- Stay up-to-date on the foundation model literature
- Design reproducible experiments to verify, compare and combine ideas from the literature
- Build data exploration tools to understand correlations, sparsity, weather patterns, consumer trends…
- Add data sources to train or test datasets
- Deploy models for use in our API and platform
- Gather and act on user feedback, iterating on model capabilities to maximize customer satisfaction and impact
- Mentor and guide future team members, helping shape a high-performing science and engineering culture as the team grows
Qualifications
- Extensive ML engineering and science experience
- Experience training large foundation models
- Intimate familiarity with Python, PyTorch or Jax
- Strong drive and ambition with product and revenue impact
- Ability to dive deep into details and verify assumptions before shipping
Skills
Required:PythonPyTorchTime series modeling
Nice to have:JaxML infrastructureMultimodal data integration
Benefits
- Competitive compensation
- Generous equity
- Daily lunch vouchers
- Gym in the office
- Monthly mobility pass contributions
- Full health insurance for you and your family
- Tasty caffeine in the office
Last updated Aug 26, 2026. Interested? Apply on the company site.
About The Forecasting Company
Foundation models for time series
The Forecasting Company builds planning systems based on our in-house foundation models for time series.
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