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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