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Ref: #73211

Senior ML Engineer

  • Practice Development & Integration

  • Technologies Business Intelligence Jobs and Data Recruitment Development Skills

  • Location Boeblingen, Germany

  • Salary NON 90,000

  • Type Permanent

Senior Machine Learning Engineer

Your New Career

As a Senior Machine Learning Engineer, you will be part of a global team developing distributed sensing solutions that help optimize critical infrastructure, protect people, and safeguard the environment. Using advanced sensing technologies combined with machine learning, the team delivers reliable real-time insights across assets such as pipelines, power cables, and railway systems.

In this role, you will contribute to solutions deployed worldwide, working in a collaborative, cross-disciplinary engineering environment that values technical rigor, long-term quality, and practical innovation.

Your Responsibilities

  • Turn machine learning proof-of-concepts into robust, production-ready systems for real-time analysis on edge devices and backend platforms
  • Lead the design and implementation of scalable ML pipelines and data processing components for high-volume sensor data
  • Drive engineering best practices within the team
  • Build and maintain CI/CD workflows and automated testing for ML applications, ensuring reliability and reproducibility
  • Collaborate closely with data scientists, platform engineers, data engineers, and domain experts to shape system architecture and integrate ML solutions into the overall product landscape

Your Profile

  • Degree in computer science, machine learning, or a related field, or equivalent practical experience
  • 5+ years of professional experience in software engineering or ML engineering, including production ML or data-intensive systems
  • Strong programming skills in Python, with the ability to write structured, maintainable, and efficient code
  • Advanced programming skills in at least one statically typed language (e.g., C++, Rust, Go, or Java)
  • Deep understanding of the MLOps lifecycle, including data and model versioning, deployment, monitoring, and continuous improvement
  • Experience with containerization (e.g., Docker) and CI/CD pipelines, along with modern testing practices

Nice to have:

  • Experience operating ML systems in production, including monitoring model performance, drift detection, and incident handling
  • Experience with real-time or near-real-time systems, streaming data, or IoT environments, including edge deployment constraints

What’s Offered

  • Challenging and impactful work using state-of-the-art technology
  • Open, collaborative, and respectful working environment
  • International, team-oriented culture
  • Competitive compensation and benefits, including flexible working hours
  • Opportunities for personal development, career growth, and performance-based incentives
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