MLData Infrastructure Engineer

Do you want to dive in the fast-growing industry of drones and get a rewarding experience in a dynamic scale-up environment

At Flyability we believe that robots should be sent into hazardous places and dangerous environments instead of humans. To support our belief we created Elios the worlds first collision-tolerant flying robot that can safely enter survey and inspect confined spaces so that people dont have to. With more than 150 employees and 1500 customers Flyability is the market leader in the UAS indoor inspection industry. Joining Flyability is not just taking on a new job; it is seizing the opportunity to improve the lives of millions of people and contribute to the future of robotics.

To complete our creative and dynamic team in Lausanne we are seeking a:

ML/Data Infrastructure Engineer (100%)
Ideal starting date: as soon as possible

Your role:

As a member of the Autonomy team you will build and operate the data and ML infrastructure that turns data collected by our inspection drones into better AI capabilities.

You will own the workflows connecting data collection preparation and labeling training evaluation and model deployment. You will work closely with our Spatial AI engineers who develop the models and our Cloud Platform Engineer who provides the shared cloud infrastructure.

A key part of your mission will be to transform our historical and continuously growing datasets into a structured versioned reliable and accessible ML asset enabling faster experimentation and reliable model delivery.

What you will own:

• Data pools & datasets: Own the infrastructure and workflows for our ML data pools and datasets from ingesting and organizing raw data to curating validating and versioning the datasets used for training and evaluation.
• Data & labeling infrastructure: Host in-house labeling tools and manage annotation workflows ensuring seamless data flows between Spatial AI engineers and external labeling partners.
• Training infrastructure: Automate and maintain the infrastructure and workflows for ML training evaluation experiment tracking and reproducibility.
• Model lifecycle: Build the tooling and automation to move models smoothly from training and validation to reliable deployment.
• ML monitoring & feedback: Monitor training and model performance connecting production data and failure cases back into the ML development loop.
• ML developer platform: Provide the tools documentation and workflows that enable Spatial AI engineers to go from data to deployable models collaborating with the Cloud Platform Engineer.

Your profile:

• 3 years of experience in data engineering MLOps ML infrastructure or related software engineering.
• Strong Python and software engineering skills with experience building production-grade systems.
• Hands-on experience with data storage databases and data processing including designing data structures and efficiently querying transforming and managing large datasets.
• Practical experience with AWS particularly S3 and cloud-based compute and storage.
• Experience with the ML lifecycle including some combination of dataset/model versioning experiment tracking training orchestration model registries or ML CI/CD.
• Experience working with ML datasets including curation versioning annotation and data quality.
• Experience with tools such as Docker CI/CD workflow orchestration or infrastructure-as-code.
• Strong understanding of the practical needs of ML engineers and the ability to build infrastructure that makes their work faster and more reproducible.
• Strong ownership and problem-solving skills with the ability to take an ambiguous problem from architecture to production.
• Proficiency in English; French is a plus.

Nice to have:

• Experience with MLflow DVC SageMaker or similar MLOps technologies.
• Experience with annotation platforms and external labeling teams.
• Experience deploying ML models to embedded or resource-constrained platforms.
• Experience orchestrating pipelines for fine-tuning evaluation and low-latency serving of Language Models.

Perks & Benefits Youll Love:

• Enjoy 25 vacation days per year plus all public holidays to recharge and explore
• Additional days off are granted based on your seniority with us up to 5 days.
• Stay secure with comprehensive accident insurance covering medical treatments and hospitalization
• Work your way with flexible schedules and the option to work remotely up to 2 days per week
• Boost your well-being with discounts on gym memberships and sports events
• Access exclusive benefits through Swibeco our platform that offers discounts and rewards at a wide range of retailers and services.
• Connect with your team at exciting events like our ski weekend summer barbecue and after-work gatherings

and so much more! Apply now to discover all we have to offer.

Flyability is a Swiss company with over 10 years of experience that values independent thinking combined with a collaborative spirit. Every day you will have the opportunity to share your ideas and contribute to solving problems. We all work together and each voice is considered as we collaborate to achieve our goals.

Ready to join

We know the confidence gap and impostor syndrome can get in the way of meeting spectacular candidates so please dont hesitate to apply regardless of your past experience or resume wed love to hear from you.

Automated Screening Notice: Please note that Flyability uses automated eligibility questions as part of our initial screening process. If your application does not meet these mandatory requirements it will be automatically excluded from further consideration. If you submit an application and believe it was incorrectly excluded by the system you have the right to request a manual review. Please reach out to our HR team at to request human intervention.

Required Experience:

IC