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Jobs/Machine Learning Engineer Role/Malt - Senior Machine Learning Engineer
Malt

Malt - Senior Machine Learning Engineer

Remote - France+ Equity1w ago
RemoteSeniorEMEAArtificial IntelligenceData AnalyticsMachine Learning EngineerCTOClose

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Requirements

• Interview with your future manager Marc 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 Claire our CTO, to discuss Malt’s long-term vision • Malt is the perfect space to thrive personally and professionally 💫 • Onboarding: 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 Paris • Equity: Every Malter is entitled to stock options • Malt sabbatical: Every three years, all Malters are entitled to a one month fully paid sabbatical leave • Free books: 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 • Team building events organized every year • Ready? Get your ticket to Malt 🪐 • At Malt, we are committed to fostering an inclusive and diverse workplace. We recruit based on skills, experience, and potential, without any form of discrimination related to age, gender, sexual orientation, ethnicity, religion, or disability. Our mission is to create a work environment where everyone feels valued, respected, and safe to thrive. • Your profile may be subject to background screening. For more information see our candidate privacy policy.

Responsibilities

• 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

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