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Full-Time

Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Jan 15, 2026. Zero Point Motion scores B on the Alion truth index.

Overview
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0 The future of precision is being built today. LINKEDIN FOLLOW US ON X Unlike traditional sensor companies, we challenge the norms of development, fabrication, and scaling.
Backed by Science Creates

Zero Point Motion is building a fundamentally new class of inertial sensors.

This role exists to bridge inertial hardware and navigation software in the real world - not by masking hardware limitations with increasingly complex algorithms, but by using mathematics, code, and physical testing to make the hardware itself better.

If you believe great inertial hardware should simplify sensor fusion, not require endless compensation, this role is for you.

The Role

As an Inertial Sensor Fusion Engineer, you work hands-on with inertial sensors, real motion, and real data. 

You will: 

  • understand inertial behaviour in practice, 

  • identify where hardware limits drive software complexity, 

  • guide the development of sensors that are easier to calibrate, integrate, and deploy. 

This is not a purely software role. You will be in the lab, not just analysing logs. 

What You’ll Do

Sensor fusion & navigation

  • Work with inertial sensors inside real navigation and sensor fusion stacks.

  • Apply concepts from inertial navigation, SLAM, state estimation, and filtering (EKF / UKF).

  • Develop intuition for what defines a high-quality inertial sensor, including noise, bias, bandwidth, dynamic range, latency, and synchronisation.

Hands-on testing & calibration

  • Perform inertial testing and calibration using industry-standard equipment (e.g. rate tables, shakers, multi-axis platforms).

  • Apply and refine calibration procedures covering bias, scale factor, misalignment, temperature effects, and dynamics.

  • Understand how calibration assumptions affect downstream fusion performance.

Mathematics, data & analysis

  • Work comfortably with linear algebra, probability, estimation theory, and coordinate frames.

  • Analyse large real-world inertial datasets and understand how errors propagate through navigation stacks.

  • Identify when software is compensating for hardware shortcomings.

Coding & implementation

  • Write high-quality code in:

    • C (performance-critical or embedded-adjacent work),

    • Python (analysis, tooling, prototyping).

  • Build self-sufficient pipelines for data ingestion, processing, and visualisation.

  • Produce clear plots that explain behaviour and failure modes.

Systems-level work  

  • Work with sensors mounted on real platforms (stationary setups, robots, motion systems). 

  • Understand how mounting, timing, and synchronisation affect performance. 

  • Bridge hardware realities with software abstractions. 

Hardware-first mindset 

  • Use sensor fusion to expose hardware weaknesses, not hide them.

  • Be comfortable saying: “This should be fixed in hardware.” 

  • Provide clear, quantitative feedback to hardware teams on which specs matter.

Required Background

You bring:

  • Experience with sensor fusion, inertial navigation, SLAM, or robotics.

  • Hands-on experience using inertial sensors in real systems.

  • Comfort with inertial testing and calibration (or strong ability to learn quickly).

  • Strong mathematical foundations.

  • Excellent coding skills in C and Python.

  • Experience handling large datasets and coordinate transformations.

  • Interest in navigation, autonomy, and real-world systems.

Who This Role Is For

This role is for someone who:

  • Enjoys working across hardware and software.

  • Is comfortable with test equipment, fixtures, and calibration procedures.

  • Wants to understand inertial sensors at a deep, physical level.

  • Is frustrated by overly complex fusion stacks compensating for weak sensors.

  • Wants to help create inertial hardware that software engineers love.

What This Role Is Not

This is not:

  • a purely software or simulation role,

  • a theoretical estimation research position,

  • a job detached from physical testing.

You will be in the lab.

What Success Looks Like

After 6-12 months:

  • ZPM understands inertial performance from silicon to system.

  • Calibration procedures are robust, repeatable, and trusted.

  • Hardware teams receive clear guidance on what improves navigation performance.

  • Fusion stacks are simpler because the hardware is better.

  • Demos clearly show why ZPM inertial sensors are different.

Working with us

  • Compensation: Our framework is built on fairness and transparency, with regular reviews to reflect growth and performance. 

  • Benefits: Share options, pension, and private medical insurance.  

  • Culture: A deep-tech rocketship backed by leading investors. We’re building breakthrough technology with real commercial impact. Pace is high. Standards are higher.

Zero Point Motion is determined to foster belonging and empowerment at work. We are committed to providing a work environment where there’s a zero-tolerance approach to discrimination, and everyone is treated with respect. Equity, diversity and inclusion are central to our mission, and we strongly encourage candidates of all different backgrounds and identities to apply. If you need assistance or an accommodation due to a disability, please contact us. 

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