(Senior) AI & Data Science Engineer (m/f/d)

EnOcean | IoT / wireless sensor solutions

2h 57m ago

Hybrid

Full Time

Germany, Netherlands

At EnOcean, we are passionate about driving innovation and creating IoT solutions that positively impact our world. We pioneered batteryless, energy-harvesting wireless sensors and built platforms that enable efficient sensing, tracking and data-driven solutions across industries such as building automation, logistics, healthcare and industrial IoT.
Our platforms combine large-scale data processing with AI-enabled analytics and automation to deliver reliable, customer-centric solutions. We turn complex telemetry and operational data from energy-efficient devices and connected systems into actionable insights, with transparency, robustness and long-term maintainability.
Security, data protection and the responsible use of advanced technologies, including AI, are integral to how we design, build and operate our systems.
#LI-Hybrid

As an AI & Data Science Engineer (m/f/d) you will work on the intelligence layer of EnOcean's cloud platform: the algorithms, analytics and AI assistants that turn raw radio signals and sensor events into positions, insights and answers. You will join a small, close-knit team, where you can see the effect of your work in production.
Everything we build starts with a customer's problem. You will work with customers and product colleagues to understand what they really need, and turn that into the right architecture, algorithms and insights. Behind that sit two connected sides. On the data science side, we turn device, radio and sensor data into actionable context and models. On the engineering side, we design real-time stream processing that runs reliably in production, at the scale of millions of events per day and with clear latency requirements. You will contribute to both, with the emphasis depending on your background.
We are hiring at mid-to-senior level, and the scope grows with your experience. As a mid-level engineer you own well-defined components with senior colleagues close by. As a senior engineer you also help set the technical direction of our AI and data science work, review designs and support colleagues in their growth. You will take over established, production-proven systems, keep them healthy, and build what comes next.
We also use AI as part of how we build software. Some of our code is drafted with the help of coding agents working from written specifications, which makes writing clear specifications, sound judgement and careful review as valuable as writing code yourself. You will already have experience working this way, and we will help you take it further, with training, time to experiment and colleagues who share what works.
The position can be based in Munich, Germany (EnOcean GmbH) (permanent contract), or Utrecht, the Netherlands (Undagrid B.V.) (one-year contract, intended to become permanent). We are recruiting for one role and will hire one candidate. The employment contract will be concluded with the local entity at the selected location. The role is advertised in both countries. Please apply only once and indicate your preferred location.

Customer solutions: Work with customers and product colleagues to understand their needs and the problem behind the question, and translate them into architecture decisions, algorithms and insights customers can act on.
Data science: Turn device, radio and sensor data into actionable context and models. This includes algorithms that estimate position and movement from noisy Bluetooth, Wi-Fi, cellular and GPS data, using filtering, clustering, physical models and honest accuracy estimates.
Data science: Build LLM-based assistants and agents on top of our platform data, with tool use, planning, memory and semantic search, and create the evaluation that keeps them trustworthy: datasets, metrics and regression tests.
Real-time engineering: Design and build stream processing for production at scale, with defined throughput and latency requirements. You work in layered pipelines from raw device data to business-ready results, such as occupancy, people counting, energy and air-quality calculations, asset health and monitoring, including replay of historical data.
Bring prototypes to production together with the platform team: services with clear interfaces, tests and monitoring.
Apply secure-by-design principles in everyday work, including dependency hygiene and vulnerability management.
Write clear specifications, work with AI coding agents where they help, and review the result, whether written by colleagues or agents.
Collaborate with backend, firmware, frontend and support colleagues, and explain trade-offs to people outside data science.

Several years of professional experience (around 4 years or more) applying data science or machine learning in production, with strong Python and the scientific Python stack.
A customer-focused way of working: you understand what customers really need, turn that into sound technical choices, and explain your results clearly to non-specialists.
A solid mathematical foundation, for example in statistics, signal processing, optimisation, probabilistic filtering or clustering.
Experience taking analytical or ML work into production, together with engineers: pipelines, testing and monitoring.
Good working knowledge of data-intensive systems: time-series data, SQL or document databases, and real-time event streaming such as Kafka, with an understanding of throughput and latency trade-offs.
Rigorous evaluation habits: you define metrics, build test sets and know how easily results can fool you.
Experience building with large language models (prompting, retrieval, tool use and evaluating output quality), or real curiosity and willingness to learn.
Day-to-day experience working with AI coding assistants or agents: writing clear specifications, steering the agent and reviewing generated code with a critical eye.
Awareness of security best practices, and comfort working in a security-regulated environment.
A pragmatic, collaborative mindset: you value clarity, robustness and maintainability over unnecessary complexity.
A degree in computer science, data science, physics, mathematics, electrical engineering or a related field is welcome; equivalent experience counts just as much.

Experience with positioning, geospatial data, radio propagation or sensor fusion.
Background in IoT, BLE or telemetry platforms.
Hands-on experience with a stream-processing framework, or with designing stateful real-time pipelines.
Experience deploying and operating services on Kubernetes.
Experience with self-hosted models, GPU inference or MLOps practices.
Ability to read TypeScript or Node.js code.

Don't tick every box? Please apply anyway. We would rather hear from you than miss a good fit.

Python and the scientific Python stack, with Node.js for real-time services · Kafka event streams and stream processing · sharded document and time-series storage in MongoDB, plus SQL · gRPC and schema-managed contracts between services · LLM agents with tool use, semantic search and automated evaluation, on hosted and self-hosted models · Kubernetes and infrastructure as code on AWS · automated quality and security checks in CI · AI-assisted development built on written specifications and independent review.

Stability
Become part of a growing company that has driven innovation since 2001.
Autonomy & Influence
In a small team, your ideas matter and you shape the platform directly.
Professional Development
Training, workshops and certifications, with a clear path towards senior responsibilities and technical leadership.
Onboarding
A structured onboarding programme and a colleague to guide you through your first months.
Flexible Working Hours & Remote Working
Flexible working hours and the option to work remotely, with a culture that supports work-life balance.
Technology
Modern equipment, and the AI tools you need to work effectively.
Fantastic colleagues
A collaborative, highly skilled and motivated engineering culture.
Equal opportunities
EnOcean welcomes applications from everyone, regardless of gender, age, origin, religion, disability, sexual orientation or background. If you need any adjustments during the application process, please let us know and we will arrange them.

We would rather see how you build than read your CV. Please submit a short technical presentation of a software or data science project you developed yourself. Tell us what you built, why you made the choices you did, and how it works. Choose a project you can walk us through in detail.
Present it in the format that suits you best:

Video – up to 10 minutes, shared as a link to the platform of your choice. We recommend this format: it shows best how you think and explain.
Written document – a technical write-up with diagrams and code samples.

Please do not share confidential material from current or former employers. Applications without a technical project presentation in one of these formats unfortunately cannot be considered.

We keep the process transparent and will tell you after each step whether we continue.
1. Introduction meeting – A first conversation about you, the role and EnOcean.
2. Technical deep dive – A discussion with future colleagues about your experience and approach to technical problems. Some preparation may be involved; we will share the details in advance.
3. Company fit meeting – A conversation with colleagues from across relevant departments about how we work together.
We will let you know the outcome after each meeting, and each stage involves a few more colleagues so you get to know the people you would work with.

Required Skills

pythonkafkamongodbsqlkubernetesnode_jsgrpcaws

Required Languages

🇬🇧 English