Machine Learning Engineer
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("Company in San Francisco, United States"), this listing's salary midpoint is about 90% lower. The offer sits below the benchmark range (€10,128–€16,277). The listed pay band (€1,168–€1,564) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 1 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Machine Learning Engineer | €11,159/per month | €16,639/per month | €21,189/per month |
| Company in San Francisco, United States | €10,128/per month | €13,203/per month | €16,277/per month |
Join Eight Sleep as a Machine Learning Engineer focused on building consumer-facing AI systems for personalization, coaching, and sleep intelligence. You will work across data, modeling, product, and engineering to translate research into reliable, measurable improvements for members, with end-to-end ownership from problem framing to production deployment and iteration. Responsibilities include building and deploying ML models to improve sleep experiences (personalization, prediction, behavior understanding), applying foundation-model capabilities to product workflows (LLM + tools/RAG, multimodal modeling, policy learning), developing user behavior models from longitudinal signals, designing evaluation strategies, productionizing models with scalable pipelines and monitoring, and collaborating with cross-functional teams to ship high-impact features.
Job Details
Responsibilities
- Build and deploy ML models that improve sleep experiences through personalization, prediction, and behavior understanding.
- Apply and adapt foundation-model capabilities to real product workflows (LLM + tools/RAG, multimodal modeling, policy learning).
- Develop user behavior models that connect longitudinal signals to actionable interventions - grounded in robust experimentation and measurement.
- Design evaluation strategies and partner with Product to run high-quality online experiments.
- Productionize models: scalable training/inference pipelines, model monitoring, drift detection, alerting, and continuous improvement loops.
- Collaborate with cross-functional partners (Product, Mobile, Backend, Clinical) to scope requirements and ship high-impact features.
Requirements
- 2+ years building ML systems in production, ideally for consumer-facing products.
- Strong ML fundamentals across supervised learning, sequence/time-series modeling, and modern deep learning.
- Hands-on experience with large-scale model training and evaluation (PyTorch/TensorFlow/JAX), and strong Python engineering practices.
- Experience with personalization systems (ranking/recommendations, segmentation, lifecycle modeling, propensity/behavior modeling, causal/experiment-aware thinking).
Skills & Technologies
Benefits & Perks
| Location | Active listings |
|---|---|
| Remote - Global | 2 |
| Milan, Italy | 2 |
| Remote - Europe | 2 |
| San Francisco, United States | 1 |
| San Francisco, CA | 1 |
| New York, NY | 1 |
| Role type | Active listings |
|---|---|
| Senior Product Designer | 1 |
| Data Scientist | 1 |
| Video Editor | 1 |
| Lead Mechanical Design Engineer | 1 |
| Role level | Active listings |
|---|---|
| Senior | 3 |
| Mid-Level | 1 |
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