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Munich - Berlin - London - Paris
Actively hiring, first seen by us todayYou will own problems end-to-end: read the literature, prototype on real recorded data, push to the edge, watch it run.
Write clean Python, and are willing to pick up Rust where the deployment target demands it.
You will work in a small research team alongside RF and hardware engineers and the operators using the system.
At Helsing you will work at the intersection of machine learning and signal processing on RF data, helping build the AI capabilities inside our electronic warfare systems: models that detect, classify, and reason about RF signals in congested, contested spectrum. The data is messy, irregular, and adversarial. Output runs on real platforms, under hard latency and compute budgets. What you build has to survive contact with the deployment target. You will own problems end-to-end: read the literature, prototype on real recorded data, push to the edge, watch it run. You will work in a small research team alongside RF and hardware engineers and the operators using the system. Current focus areas include self-supervised representation learning on signal data, deinterleaving and emitter identification, mode recognition, and anomaly detection on embedded hardware.
Are comfortable on irregular, noisy sequence data: temporal models, self-supervised or contrastive methods, calibration under distribution shift. Write clean Python, and are willing to pick up Rust where the deployment target demands it. Read papers and reimplement them. You can tell which results will hold up and which won't.
You should apply if you - Hold a PhD (or have an equivalent research track record) in ML, signal processing, physics, electrical engineering, or a related field, with publications at NeurIPS, ICLR, ICML, ICASSP, or similar venues. - Have shipped non-trivial ML into a real product - not just notebooks. You know what breaks between research and deployment.
From the employer’s posting.
Helsing is a defence AI company with the mission is to protect our liberal democracies.
In the employer’s words · Read in context
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Day 0
Early. Similar jobs usually come down between day 7 and day 57.
From 10,564 similar postings that came down. Coming down is not always a hire.
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- Are comfortable on irregular, noisy sequence data: temporal models, self-supervised or contrastive methods, calibration under distribution shift. - Write clean Python, and are willing to pick up Rust where the deployment target demands it. - Read papers and reimplement them. You can tell which results will hold up and which won't.
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Yes. We’ve followed one other AI Research Engineer - ML & Signal Processing job there since April 2026. It came down after 204 days.
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Helsing is a defence AI company with the mission is to protect our liberal democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards. We believe we have a responsibility to be thoughtful about the development and deployment of powerful technologies like AI and take this responsibility seriously.
We are an ambitious and committed team of software and deployment engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams – and apply their skills to solve the most complex and impactful problems today.
We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications.
At Helsing you will work at the intersection of machine learning and signal processing on RF data, helping build the AI capabilities inside our electronic warfare systems: models that detect, classify, and reason about RF signals in congested, contested spectrum. The data is messy, irregular, and adversarial. Output runs on real platforms, under hard latency and compute budgets. What you build has to survive contact with the deployment target.
You will own problems end-to-end: read the literature, prototype on real recorded data, push to the edge, watch it run. You will work in a small research team alongside RF and hardware engineers and the operators using the system.
Current focus areas include self-supervised representation learning on signal data, deinterleaving and emitter identification, mode recognition, and anomaly detection on embedded hardware.
Hold a PhD (or have an equivalent research track record) in ML, signal processing, physics, electrical engineering, or a related field, with publications at NeurIPS, ICLR, ICML, ICASSP, or similar venues.
Have shipped non-trivial ML into a real product - not just notebooks. You know what breaks between research and deployment.
Are comfortable on irregular, noisy sequence data: temporal models, self-supervised or contrastive methods, calibration under distribution shift.
Write clean Python, and are willing to pick up Rust where the deployment target demands it.
Read papers and reimplement them. You can tell which results will hold up and which won't.
Communicate research clearly to ML peers, RF engineers, and end users.
We don't expect you to arrive with deep RF expertise. A strong ML or physics background and willingness to learn the domain alongside RF colleagues is enough.
Note: We operate at an intersection where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points.
Experience with EW, SIGINT, ESM/ELINT, RWR, or radar concepts.
Familiarity with RF signal theory at a level sufficient to talk to RF engineers (modulation, propagation, antenna patterns — see modulation-schemes).
Experience deploying ML to edge or embedded hardware (ONNX, TensorRT, quantisation, profiling on constrained GPUs).
Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns
The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world
Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defence industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward
In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts
We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practise responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about
Competitive salary and VSOP options
Relocation support: up to €2,500 and 4 weeks temporary accommodation
Learning: €500/£450 yearly allowance
Health & wellness: gym membership and mental health support (Nilo.health)
Social: regular company events and monthly social allowances
Enhanced parental leave: 22 weeks fully paid for primary caregivers & 6 weeks for secondary caregivers
Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work
These are the core benefits across all locations, there may be additional benefits in certain locations.
Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation.
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Munich - Berlin - London - Paris
- Enhanced parental leave: 22 weeks fully paid for primary caregivers & 6 weeks for secondary caregivers - Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work These are the core benefits across all locations, there may be additional benefits in certain locations.
No clear work-authorization passage found. Eligibility is unconfirmed.