{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Machine Learning Engineer H/F
Role details
Job location
Tech stack
Job description
Design, build, and deliver machine learning models and pipelines in close collaboration with Data Science, Research, and Engineering teams.
- Own and evolve complex ML systems, ensuring they remain scalable, reliable, and maintainable in production.
- Drive technical excellence and best practices across the entire ML lifecycle, from modeling and evaluation to deployment and monitoring.
- Define and implement production standards that increase the quality and speed of development across the Data & ML organization.
- Translate complex business problems into robust ML solutions with measurable and durable impact on product outcomes.
- Act as a technical leader and mentor, supporting the growth of ML practices and elevating the skills of less experienced team members, First call with, our Tech Talent Acquisition Manager, to better understand your background, aspirations and answer any questions you may have. (30-45 minutes)
- Interview with your future manager to delve into your experience and the specifics of the role. (45-60 minutes)
- Technical discussion about machine learning with some of your future colleagues (1h)
- Take home coding test: 2 hours (coding assistant welcomed) or optional if you have enough open source projects online.
- Final interview with our CTO, to discuss Malt's long-term vision
Before easing into your new role, you'll spend your first week learning about our culture, products, and services with other new joiners at our office in ParisEvery Malter is entitled to stock optionsEvery three years, all Malters are entitled to a one month fully paid sabbatical leave If you're interested in learning more about any topic relevant to Malt's business, just tell us the books you'd like to read, and we'll order them for you-without any questions asked or approval processes to follow events organized every year
Requirements
5+ years of experience in software engineering and deploying machine learning models in production environments.
- Ideally educated to a high level in Computer Science, Mathematics, Data Science, or a related quantitative field.
- Strong knowledge of a programming language, ideally Python.
- Experience with ML libraries (Pytorch, Tensorflow, XGBoost, Scikit-Learn, LightGBM, ...).
- Good knowledge of SQL
- Expertise in search, recommender systems, or NLP including LLM to influence system design and long-term technical strategy.
- Fluent in English, with the ability to distill complex ideas clearly across teams.