Software Engineer, MLOps – Production-Grade ML Pipelines

Job Description

Ecorobotix SA, a Swiss B-Corp company headquartered in Yverdon-les-Bains, offers innovative, robotic solutions to lessen the environmental impact of agricultural activities. We develop ultra-precise spraying technologies powered by artificial intelligence, allowing farmers to significantly reduce the use of chemicals in their fields. Join our dynamic, international team, and together, let's make agriculture more sustainable!

General Objective of the Role

The MLOps Engineer is responsible for ensuring the reliable industrialization, deployment, and operation of machine learning solutions by combining software engineering best practices with MLOps and DevOps expertise. The role focuses on transforming research code into production-grade applications, developing and maintaining automated ML pipelines, supporting model lifecycle management, and ensuring the stability, scalability, and efficiency of machine learning infrastructure and deployment environments.

Reporting Line

• Reports directly to the AI Solution Manager
• Works within the Digital Agronomy Department

YOUR FUTURE ASSIGNMENTS

We are looking for a developer with strong MLOps expertise to join our Model Production team. In this role, you will balance software engineering excellence with the operational management of machine learning systems, ensuring that ML pipelines remain reliable, scalable, and efficient. You will be responsible for:

• Transforming experimental research code into robust, production-grade software architectures.
• Building, maintaining, and optimizing machine learning pipelines using Airflow.
• Automating model training, validation, deployment, and monitoring processes.
• Managing day-to-day MLOps and DevOps activities across the ML infrastructure stack.
• Participating in code reviews and promoting software engineering and MLOps best practices within the team.

EXPERIENCE REQUIRED

Required Technical Skills

• Orchestration: Airflow (DAG design, maintenance, and operational ownership)
• CI/CD: GitLab CI, Jenkins, or similar
• ML Frameworks: PyTorch (understanding to facilitate model integration)
• Software engineering: familiarity with clean code and good practices
• Nice to have:
• Experiment tracking tools (MLflow, ClearML, etc.)
• Kubernetes or container orchestration experience

Desired Profile

• Experience: Minimum 3 years in software development, with hands‑on MLOps or DevOps exposure.
• Mindset:
• Operational: You automate everything and make workflows reliable.
• Pragmatic: You know clean code matters but shipping working pipelines matters too.
• Collaborative: You know how to work with research and operations teams to bridge the two worlds, across distributed locations.
• Communicative: You express ideas clearly, collaborate effectively in writing and async, and enjoy working as a team.
• Leadership: You drive initiatives forward end to end.
• Languages: Fluent in French and English.