AI Research Engineer - 3D Computer Vision

Helsing; United States; Remote; USD 140,000 - 250,000; Full time

Benefits offered by this job

Competitive salary and VSOP options

Relocation support

Learning: €500/£450 yearly allowance

Health & wellness: gym membership and

Social: regular company events and $,

Job summary

Helsing in the United States seeks a senior research engineer to advance scene understanding, localisation, and 3D reconstruction for defence AI applications. You will develop and benchmark pipelines, push state‑of‑the‑art geometric deep learning, and adapt methods to edge hardware and real‑world data.

Collaborate with cross‑functional teams to integrate outputs into navigation and decision‑making tools, publish results, and contribute to the roadmap across projects.

Qualifications

• MSc in computer science, ML, robotics or related field with experience designing and evaluating AI systems.
• Hands-on experience developing localisation, scene matching, or 3D reconstruction systems.
• Experience with geometric vision and deep learning, including learned feature matching, place recognition, SLAM, VIO or NeRF; domain adaptation or model compression.
• Solid software engineering skills, Python, and deploying AI software to production with testing, QA and monitoring.
• Excellent communication skills and ability to present research clearly.
• Passion for current research and reimplementing state-of-the-art approaches in geometric deep learning, SLAM, and 3D vision.
• PhD in CV/ML/robotics with publications in top venues is a plus.
• Experience designing, evaluating, and delivering end-to-end AI systems on edge devices with constrained compute.
• Experience with simulators/emulators or synthetic data pipelines for geometry/localisation.
• Experience with Rust and/or C++.

Responsibilities

• Developing and benchmarking scene matching and geo-registration pipelines robust to challenging conditions.
• Building and evaluating SLAM/visual odometry/structure-from-motion for deployable platforms.
• Researching geometric deep learning or feature matching methods for concrete use cases.
• Collaborating with product/deployment teams to integrate outputs into navigation/decision pipelines.
• Develop computer vision models and pipelines using state-of-the-art methods and architectures; design experiments and benchmarks.
• Adapt techniques to target hardware and constraints of downstream ML/AI tasks.
• Contribute to impactful projects and collaborate across teams.

Education

MSc in computer science / machine learning / robotics or related field

Experience designing and evaluating AI systems

Excellent communication skills

Tools

Python

Rust

C++

NeRF

SLAM

Geometric deep learning

Job description

Описание:

Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards. As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously. We are an ambitious and committed team of 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. 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 we deliver AI-based capabilities and the enabling foundation that allow machines to perceive and assist human decision‑making. You will have the unique opportunity to shape AI capabilities in one of the most challenging sectors, where high generalisation capabilities need to be paired with hardware constraints and robustness against adversarial attacks. You will be part of a computer vision team specialising in scene understanding and localisation, responsible for building systems for scene matching, geo‑registration, simultaneous localisation and mapping (SLAM), and 3D reconstruction. You will develop and extend state‑of‑the‑art architectures and pipelines, design rigorous experiments, and conduct benchmarks to evaluate and improve real‑world performance, including adaptation to the compute constraints and operational requirements of downstream deployments. You will collaborate across research, engineering, and product teams on high‑impact projects.

Задачи:

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. 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.

Требования:

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. 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‑magnitud e 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.

Условия:

• 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.