Senior MLOps Engineer (m/w/d)
Flexa · 🌍 München
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- Pay clears the visa salary barStated pay (€ 95,000 – 115,000 per year) clears the Germany EU Blue Card threshold of €50,700. Source: https://www.make-it-in-germany.com/en/visa-residence/types/eu-blue-card, rules effective 2026-01-01.
- Confirmed live todayWhen a source last listed this job as open.
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No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.
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Sponsor Radar — Flexa
This employer posted directly and does not match a government sponsor register.
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About the role
Short Facts • Location: Munich, Germany • Employment Type: Full-Time, indefinite term • Salary Range: € 95,000 – 115,000 per year gross, depending on seniority level • Office First work setup • Language Requirement: C1 Level English Your Responsibilities • Act as the technical bridge between data science and software engineering, helping research models become reliable, maintainable production systems, and helping engineering understand what ML workloads actually need • Design and build the data and feature pipelines that support Flexa's forecasting and trading models at scale across hundreds of thousands of distributed systems • Leverage Flexa’s deployment, orchestration, and serving platform to bring models into production, for both batch and real-time workloads • Establish monitoring and observability for models in production, like drift, data quality, latency, and failure modes • Partner closely with data scientists on model design and validation, bringing an engineering perspective on scalability, maintainability, and production risk from early on • Champion engineering rigor and ML best practices to foster an open, data-driven engineering culture. • Contribute to the technical roadmap, anticipating scaling needs as data volume and model complexity grow • Opportunity to guide and develop more junior colleagues through design review, code review, and structured feedback • Be part of a cross-functional team of data scientists, software engineers, and other teams across Flexa's partner ecosystem Your Profile Mandatory Requirements • University degree in an engineering or analytical field (Computer Science, Mathematics, Physics, Statistics, Engineering or a related discipline) • 5+ years of engineering experience, with significant time spent supporting or building ML systems in production • Proficiency in Python and software engineering best practices: testing, code quality, code review, CI/CD, monitoring, and modular code design • Solid working knowledge of MLOps practices: pipeline setup, deployment, monitoring • Enough fluency in ML/statistical modeling to collaborate effectively with data scientists and make sound architectural tradeoffs together • Independent, pragmatic problem-solving with strong attention to detail in a fast-paced environment • Excellent English communication and interpersonal skills • Cross-functional collaboration mindset across data scientists, software engineers, and partner-company stakeholders Skills to Set You Apart • Experience in energy, power markets, or other near-real-time operational domains • Familiarity with orchestration tools (Airflow or similar), MLOps toolchains (MLflow, Sagemaker, or similar), and streaming systems (Kafka or similar) • Hands-on experience with large-scale data tooling: Spark, Dask, or comparable frameworks • Experience designing or owning near-real-time analytics and/or ML workflows, including observability • Track record of taking models from research into production on AWS or comparable cloud provider This won’t be the right role for you if… • You don’t have the habit of defining your own tasks and have a preference for working in clearly separated functions Benefits • Virtual Share Options: we offer virtual share options to all our employees • Professional Development: annual development budget of €3,000 for coachings, trainings, books, and similar • Health & Sport Subsidy: company-subsidised sports facilities membership, or Public Transportation Subsidy • Lunch/Dinner Allowance Vouchers: allowance for meals on working days as digital meal vouchers • Work Equipment: MacBook or Windows laptop, iPhone (also for private use), and an ergonomic workplace setup with company-funded access to leading AI developer tools • Regular