Product ML Engineer
Machine learningHybrid — Paris
Published on 2026-10-28
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.
About this role
Own short, high-impact machine learning projects embedded in a product team, from problem framing through launch and production monitoring. Choose between building or fine-tuning models and integrating existing solutions, with success measured by customer and business impact.
About the company
Photoroom provides advanced photo editing solutions and tools designed to enhance e-commerce and marketing experiences. The company serves businesses by enabling seamless image background removal and other editing functionalities through its platform.
The team
Embedded in one of the SMB, Scaler, or Enterprise product teams, collaborating with the ML team.
Stack
PyTorchTensorFlowJAX
What you'll do
- Frame ML problems and deliver solutions end to end, from approach selection through production launch.
- Decide whether to build or fine-tune models or integrate external models, APIs, and libraries.
- Write production code in the product team's codebase and iterate based on customer feedback.
- Evaluate, monitor, and investigate the performance of ML features in production.
What we're looking for
- At least 2 years of experience building and shipping ML-powered products.
- Strong experience with PyTorch or an equivalent framework.
- Ability to fine-tune vision or diffusion models, design evaluations, and debug training runs.
- Comfortable writing maintainable production code and owning ambiguous projects.
- Fluent in English.
Nice to have
- Experience shipping generative image or diffusion models to production.
- Experience evaluating third-party AI APIs against internal alternatives.
- Experience at a fast-growing startup or embedded in a product team.
Benefits
- Meaningful equity.
- Hybrid work from the Paris headquarters.
- Visa sponsorship and relocation support up to €10,000.
- MacBook Pro and home office setup.
- 30 days of annual leave.
- Private healthcare.
- Company off-sites and team retreats.
- English and French language lessons.
Hiring process
- Screening with an ML researcher or engineer.
- Home technical assignment and team review.
- Culture-fit interview and meet the team.
- Reference check and offer.