Job Title: Machine Learning Engineering Manager
Location: Luxembourg, Luxembourg
Job Type: Permanent
Salary: €130,000 – €160,000 + Share Options + Relocation bonus
Working setup: Full time, 4 days per week onsite.
Language: English
Industry Sector: New Space, Earth Observation, Satellite Imagery, Remote Sensing
Candidates must have the right to work in the EU
Introduction:
Talent-Relay has partnered with Global Earth Observation client to onboard an experienced Machine Learning Engineering Manager lead a team of scientists and engineers applying advanced machine learning and deep learning techniques to satellite imagery and geospatial data.
Our partner leverages satellite imagery, thermal infrared and multi-spectral data, to deliver valuable insights into agriculture, climate, and commercial clients.
The team builds advanced algorithms that turn satellite data into actionable insights, ensuring pipelines are reliable, and reproducible.
You will guide the development of scalable models for image classification, segmentation, and data fusion, using high‑performance and cloud platforms
Key Responsibilities:
- Lead & inspire a team of ML engineers tackling Earth Observation challenges.
- Build scalable models for classification, segmentation, and feature extraction.
- Innovate in thermal and multispectral data fusion with cutting‑edge deep learning.
- Partner with product and engineering to deploy models seamlessly into production.
- Champion MLOps best practices: versioning, monitoring, retraining.
- Audit architectures, pipelines, and code for technical excellence.
- Contribute to research, proposals, and represent Hydrosat externally.
- Set & track team objectives with measurable results.
- Coach engineers on growth and technical mastery.
- Recruit & retain top talent to strengthen the team.
Required Qualifications, Skills and Experience:
- Master’s degree in Computer Science, Machine Learning, Physics, Mathematics, or related field.
- 10+ years in data science, ML, or computer vision, with 2+ years leading ML teams.
- Deep learning expertise: CNNs, transformers, self‑supervised learning.
- Strong MLOps skills: CI/CD, model serving, experiment tracking.
- Hands‑on with ML frameworks: PyTorch, TensorFlow, Scikit‑learn.
- Cloud & containers: AWS, GCP, Azure, Docker, Kubernetes.
- Proven ability to build and deploy ML models at scale.
- Excellent communication and organizational skills; fluent in English.
Bonus Skills:
- PhD in a relevant field.
- Experience in image analysis and geospatial data.
- Familiarity with thermal infrared and multispectral satellite data.
- Background in high‑performance computing environments.
- Prior work integrating ML/DL into production EO pipelines.