Help us make machine learning work where it really matters.

At Helin, we build technology that runs where dashboards can’t — out in the field. From offshore drilling platforms to smart energy systems, our clients rely on real-time data, edge computing, and resilient infrastructure to keep people safe and operations running.

That’s where you come in.

We’re looking for a backend systems engineer who’s excited to work at the intersection of ML, cloud, and edge. Not to train fancy models in the lab — but to make sure those models actually run in places with spotty connectivity, high stakes, and zero room for error.

You’ll be joining a small, sharp team that’s building the backend systems and tools that power real-time AI across energy and industrial sites. You’ll solve problems like:

• How do we remotely deploy ML updates to rigs in the North Sea?
• What does observability look like when you can’t SSH into a machine?
• How do we package, version, and test ML applications for field rollout?

If you like messy, high-impact engineering and want to build systems that move from dev to dock without drama — this is your playground.

• Build backend systems that support ML model deployment in industrial environments
• Develop containerized workflows for edge and cloud using Python and Docker
• Integrate NVIDIA SDKs and secure remote access setups
• Collaborate with Field Engineers to deliver reliable tooling for field deployment
• Improve system robustness, usability, and automation in every release

• 4+ years of backend engineering experience
• Strong skills in Python, containerization, and cloud platforms (AWS/Azure)
• Understanding of vision software (Image Processing/Point Cloud Data)
• Comfortable working with systems distributed across a network
• Experience building resilient backend systems for high-availability setups
• Clear communicator with structured documentation habits

Bonus if you have

• Background in industrial engineering or experience with field-deployed systems
• Exposure to computer vision systems or AI toolchains (e.g., NVIDIA SDKs)
• Knowledge of ML model deployment (but not training)
• Working experience in Nvidia Deepstream

• Location: Hybrid — 2–3 days/week in Rijswijk
• Application process: Intro call → 2-hour take-home assignment → Technical deep-dive → Final culture fit
• Timeline: Offer expected within 10 working days

Why join Helin

• Build ML infrastructure that’s used where it matters — not in demos, but in the field
• Work closely with experts across AI, field ops, and edge computing
• Get a €3,000 education budget, SARs plan, and covered commuting
• Join a diverse team of 70+ people from 30+ nationalities
• We eat lunch together, challenge ideas, and ship smart tools that scale

Please note, that only candidates living in the Netherlands with EU citizenship or equivalent will be considered as viable candidates. Working remotely is NOT an option.

Acquisition in response to this vacancy is not appreciated.

#LI-Hybrid