Machine Learning Engineer

About the Job
We are a Swiss startup leveraging AI and advanced optimization algorithms to transform logistics. Our solutions help Fortune 500 companies reduce logistics costs by more than 20% while lowering CO₂ emissions through smarter packing and freight utilization.
We are seeking a Machine Learning Engineer to help us develop intelligent optimization solutions for complex, real-world logistics challenges.
What You’ll Do
As a Machine Learning Engineer,
You will:
Design, implement, and train reinforcement learning and deep learning models for real-world optimization problems.
Work with constraint-based problems and combinatorial optimization techniques.
Translate research ideas and academic approaches into practical solutions.
Work with large and complex datasets to identify patterns, develop models, and improve optimization outcomes.
Collaborate with engineers and domain experts to integrate AI and optimization approaches into production systems.
Write clean, maintainable Python code and contribute to testing, documentation, code reviews, and development workflows.
Continuously evaluate and improve the performance, scalability, and reliability of AI-based solutions.
What We Need You to Have
Education: A Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or a related field.
Python: Strong Python programming skills and experience building software beyond notebooks and prototypes.
Machine Learning: A strong understanding of machine learning and deep learning concepts, with practical experience developing and training models.
Reinforcement Learning: A solid understanding of reinforcement learning concepts, with practical experience applying reinforcement learning to optimization problems.
Optimization: Practical experience with combinatorial optimization, operations research, or mathematical programming.
Production ML: Proven experience building, deploying, and maintaining machine learning models in production environments.
Frameworks: Hands-on experience with PyTorch, TensorFlow, or similar ML frameworks.
Problem-Solving: Strong analytical and problem-solving skills, with the ability to break down complex problems and develop practical solutions.
Research: The ability to understand, implement, and adapt research-based approaches to practical problems.
Version Control: Working knowledge of Git and modern version-control workflows.
Strong written and verbal communication skills in English.
How You’ll Work
Remote-first and results-driven: Primary working hours are CET-aligned to enable close collaboration with the team.
Research meets production: You will have the opportunity to experiment with new approaches while also working on solutions deployed in real-world applications.
Startup pace: Workload may vary by phase; we stay connected, communicate frequently, and solve problems together.
Bonus Points For

Experience with logistics, supply chain, packing, routing, scheduling, or other operational problems.
Experience with cloud platforms such as Azure or Google Cloud Platform.
Experience with API development, integration, and working with production systems.
Experience translating research ideas to implementation.
Experience working with large-scale datasets or computationally intensive problems.

Work arrangement
Yes