Job description
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We are an early-stage startup developing ‘bolt-on’ autonomy for the agricultural sector - hardware and software that turn existing tractors, sprayers, and harvesters into autonomous machines.
We fuse advanced vision/AI navigation with rugged, field-tested hardware to deliver cost-effective and intuitive autonomy that farmers can trust.
We raised our initial funding three years ago and built our core technology with a lean team of a few engineers.
We’ve proven the core technology in the field, validated market demand, and are now entering commercial trials in NZ and California - so we’re growing our engineering team over the coming months.
We’re hiring roles across software/ML, mechanical, and electronics, with multiple roles open that can be shaped around the strengths of the right candidates.
We are a small team with a lot to do, so you’ll need to be highly self-driven, able to figure things out without a detailed brief, and know when to push hard and when to be pragmatic.
The Role
We’re looking for an engineer to advance the autonomy stack that sits over existing tractors and implements - improving what we have, extending capabilities, and creating new systems where needed.
Your work will span offline routing and maneuver planning (e.g. obstacle-aware turns and trailer kinematics), real-time decision logic, and localisation improvements through better sensor fusion and modeling.
You’ll tackle problems like laneway network traversal, multi-vehicle coordination, and safety-critical autonomy logic, while developing simulation and testing frameworks to harden our navigation stack.
This role requires strong geometric, statistical and optimisation reasoning, along with a practical approach to autonomy system design,to ensure the autonomy system performs reliablyin tough field conditions.
Key Responsibilities
- Develop advanced routing algorithms, including laneway network traversal, obstacle-aware turns, and trailer-aware maneuvers.
- Refine vehicle localisation by improving sensor fusion across GPS, vision-based odometry, mapped landmarks, gyros, and encoders to reduce error margins in GNSS-limited conditions.
- Design multi-vehicle coordination and behaviour planning logic for shared tasks and safe field operations.
- Harden safety-critical logic and data pathways, with self-monitoring, fail-safes, and recovery strategies.
- Enhance implement control logic and timing for precision operations.
- Build simulation frameworks for testing routing, sensor models, and failure scenarios (e.g., GPS multipath interference).
- Develop automated calibration and vehicle dynamics modeling to improve long-term reliability.
Who You Are
We’re looking for someone with a strong mathematical and programming foundation - whether you think of yourself as an engineer, researcher, or applied mathematician.
You should be comfortable reasoning about geometry, uncertainty, and constraints, and turning that thinking into practical, reliable systems.
- Learns exceptionally fast - you can absorb unfamiliar concepts quickly and apply them effectively in new contexts.
- Strong reasoning across geometry, probability, and system constraints - you model real-world problems clearly and rigorously.
- Prototypes and iterates quickly - whether by writing code, testing algorithms, or modeling systems.
- Writes clean, maintainable C++ or Python, and knows how to structure complex logic into robust systems.
- Thoughtful about reliability - you design for edge cases, failure modes, and safety.
- May have done postgraduate work in optimisation, control, or estimation - or developed similar depth through hands-on work.
- Comfortable working without a detailed spec - you can chart a path through ambiguity and figure out what matters.
- Excited to apply rigorous problem-solving to real-world autonomy challenges, even if your past work hasn’t been in robotics.
Preferred Skills/Experience (Ticking some of these boxes is helpful)
- Motion planning, trajectory generation, or probabilistic localisation and state estimation (e.g. Kalman/particle filters)
- Data modeling, state machines, or behaviour trees
- Real-time software design, including multi-threading or pipeline parallelism
- Exposure to safety-critical software design or FMEA processes
- Freedom to innovate - minimal bureaucracy, maximum impact.
- Own systems end-to-end – from design to deployment on autonomous machinery.
- You’ll have opportunities to spend time on-site with growers in California and Bay of Plenty, shaping the technology hands-on.
Practical things
- We run a hybrid working model with mandatory days in the office.
- Our preference is a full time employee, but we’re open to contracting.
- Available to travel for up to 6 weeks at a time.
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Telecommunication & Information Technology