Machine Learning Engineer (m/f/d)

Role overview

CARRACTA is hiring a Machine Learning Engineer in Berlin to develop and operationalize machine learning solutions for enterprise environments, with a strong emphasis on scalable production systems and automotive-related use cases.

What you will do

• Build, train, assess, and scale machine learning models for production use.
• Embed intelligent models into a range of services within enterprise infrastructure.
• Develop solutions using modern technologies and frameworks with a focus on scalability, cost efficiency, and flexibility.
• Help shape and evolve the company’s machine learning architecture and contribute ideas for emerging approaches and trends.
• Create and support ML CI/CD workflows that automate data collection, data analysis, experimentation, model training, model deployment, and production monitoring.
• Develop and maintain ML services that are highly performant and able to scale reliably.

Required technical background

• Strong hands-on experience with Python.
• Experience with CI/CD tooling such as Azure DevOps or GitHub Actions.
• Practical knowledge of TensorFlow.
• Experience working with Spark.
• Familiarity with cloud platforms, especially Azure or AWS.
• Experience training machine learning models.
• Knowledge of infrastructure as code (IaC).

Preferred qualifications

• Experience with monitoring in production systems.
• Exposure to Golang.
• Knowledge of Kubernetes.
• Strong communication skills.
• Comfort working with Agile methodologies.
• Experience with Airflow.
• Background in C or C++.

Ways of working and tools

• Agile management practices including OKR, Scrum, Kanban, and broader Agile approaches.
• Version control using Git.
• Documentation and knowledge-sharing through Confluence, Wiki systems, or an internal wiki.

Work environment and equipment

• The role is based onsite in Berlin.
• Work devices are provided, including a notebook and two monitors.
• Supported operating systems include Linux, macOS, and Windows.

Benefits

• Regular personal development conversations.
• Clear opportunities for career growth.
• Mobile office options.
• Home office flexibility.
• Flexible working hours.
• Private use of company hardware.
• Open and candid feedback culture.
• Freedom to use your own tools.
• Learning accounts for development.
• Corporate discounts.
• Gym membership.
• Sport events.
• Mobility budget.

Team culture and expectations

The company values motivation, a proactive mindset, reliability, and a willingness to work collaboratively. The team operates in cross-functional Scrum teams, typically combining data engineers, software engineers, data analysts, and data scientists. The leadership style emphasizes trust, independence, and fact-based decisions rather than hierarchy.

Current focus areas

The Berlin team is working on automotive projects, including analyzing in-car user behavior to improve usability and collaborating with clients to enable machine learning in vehicles, with applications ranging from added functionality to autonomous driving.

Professional development model

Each team member receives an individual development plan aligned to their goals and the skills needed to support them. The working rhythm includes four days per week on project work and one dedicated day for personal development, such as training or education.

Additional notes from the employer

The ideal candidate is someone with the right motivation, who is proactive, understands that a strong contribution may sometimes mean delivering 80% of the ideal solution, and is dependable within the team. During interviews, the employer typically explores which tasks a candidate dislikes, how they would design their ideal role, and what they consider to be strong management.

About the company and work style

The workplace culture highlights purposeful work as seeing tangible positive impact from one’s actions. A typical good workday starts around 9:00, with no meetings until 10:00, enabling focused progress and successful team deliveries through strong cooperation.