Staff AI Research Engineer - 3D Computer Vision

Typical examples of day-to-day responsibilities include, depending on the team:

• Developing and benchmarking scene matching and geo-registration pipelines robust to challenging conditions such as changes in illumination, viewpoint, season, or sensor modality.
• Building and evaluating SLAM, visual odometry, or structure-from-motion systems for deployable platforms under real-world operational constraints.
• Researching and adapting state-of-the-art geometric deep learning or feature matching methods to concrete use cases, from local feature descriptors to learned place recognition.
• Collaborating with product and downstream deployment teams to integrate localisation and reconstruction outputs into navigation or decision-making pipelines and shape the roadmap for new capabilities.

The day-to-day

You will develop computer vision models and pipelines that leverage and extend the latest state-of-the-art methods and architectures, as well as design experiments and conduct benchmarks to evaluate and improve their performance in real-world scenarios.

You will also apply and develop techniques to adapt them to the target hardware and constraints associated to the downstream ML/AI tasks.

You will contribute to impactful projects and will collaborate with people across several teams and backgrounds.

You should apply if you

• Hold an MSc in computer science, machine learning, robotics, or a closely related field, with experience in designing, implementing, and thoroughly evaluating advanced AI-based systems.
• Have hands-on experience developing localisation, scene matching, or 3D reconstruction systems. You have iterated on models and geometric pipelines beyond benchmarks and understand what it takes to make these systems reliable under real-world data distributions and deployment constraints.
• Are deeply familiar with modern approaches to geometric computer vision and deep learning, including learned feature matching, place recognition, visual SLAM, visual-inertial odometry (VIO), or neural 3D representations such as neural radiance fields (NeRF), and have applied techniques such as domain adaptation or model compression to practical problems.
• Possess solid software engineering skills, writing clean and well-structured code in Python, and have experience deploying AI software to production including testing, QA, and monitoring.
• Have excellent communication skills and the ability to report and present research findings clearly and efficiently, both internally and externally.
• Are passionate about keeping up to date with current research and enjoy reimplementing and extending state-of-the-art approaches in geometric deep learning, SLAM, and 3D vision.

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.

Nice to have

• PhD in computer vision, machine learning, robotics, or a related field, with publications in top-tier venues (e.g. CVPR, NeurIPS, ICLR, ICCV, ICRA, IROS, ECCV).
• Experience designing, evaluating, and delivering end-to-end AI systems on edge devices with constrained compute resources.
• Experience with simulators, emulators, or synthetic data generation pipelines for geometry or localisation tasks.
• Experience with Rust and/or C++.

Join Helsing and work with world-leading experts in their fields

• 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.

What we offer

• 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

Helsing's Candidate Privacy and Confidentiality Regime can be found here .

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Source: Statistisches Bundesamt (Destatis), table; dl-de/by-2-0; StarIn's calculation