Machine Learning Engineer - Computer Vision

Lindus Health Limited; Greater London; Hybrid; GBP 70,000 - 120,000; Full time

Benefits offered by this job

Share options vesting over three years

Bupa private medical insurance

6% employer pension contribution

25 days leave plus bank holidays

Enhanced mat/pat leave

Enterprise level AI tooling

Relocation support/home office budget

Job summary

Minerva Defence seeks an experienced machine learning engineer to design, train and deploy vision-based models for autonomous vehicles. You will collect datasets, develop deep neural networks, and optimize inference on edge hardware while coordinating with flight control engineers to ensure reliable guidance.

Strong Python and PyTorch skills are essential, with experience deploying models to embedded systems and real-world hardware. Hybrid London-based work is expected.

Qualifications

• Hands-on experience training and evaluating deep neural networks on real-world image/video data.
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• Strong Python and PyTorch experience.
• Ability to deploy models to embedded hardware and on-edge compute.

Responsibilities

• Build and improve the models behind vision-based navigation, perception and guidance.
• Design and collect annotation pipelines for real and simulated datasets.
• Design and train deep neural network based computer vision models.
• Optimise models for deployment on edge compute.
• Collaborate with flight control engineers to integrate model outputs into guidance.
• Diagnose failure modes from flight data and fix via data or model changes.

Skills

Python

Deep Learning

Edge Deployment

Tools

PyTorch

Model deployment on embedded hardware

Job description

As a machine learning engineer in the computer vision team you will be responsible for designing, training, evaluating and deploying machine learning models onto a large fleet of operational vehicles.

Minerva Defence is one of the fastest-growing defence technology companies in Europe. We create the software, hardware and networking that make unmanned systems effective on the modern battlefield, all ideated, designed and manufactured end-to-end in the UK and in active use today. We are deliberately low-profile: a team of around 80, small in headcount and outsized in effect. We look for people who are not just talented but genuinely committed to the work, the team, and the purpose behind it.

You’ll join the team responsible for the vision and autonomy stack on the vehicles. The work spans navigation, perception and guidance. Engineers will be expected to operate across the full range of the problem set from collecting/designing datasets, model selection/training, optimisation for inference on-edge, flight testing on real systems and monitoring/improving operational performance.

Responsibilities

• Build and improve the models behind vision-based navigation, perception and guidance.

• Design, collect and if necessary build annotation pipelines for real and simulated datasets.

• Design and train deep neural network based computer vision models

• Optimise models for deployment on edge compute

• Work with the flight control engineers so model outputs feed reliably into guidance

• Diagnose failure modes from flight data and fix them through data or model changes

Requirements

Minimum:

• Hands-on experience training and evaluating deep neural networks on real-world image or video data

• Strong Python, plus experience with a major deep learning framework such as PyTorch

• Experience getting a model running on real hardware or in a production system

• Able to work from our London office on a hybrid basis

Preferred:

• Experience with visual navigation, visual odometry or SLAM

• Experience with object detection or classification

• Familiarity with guidance, navigation and control concepts

• Experience fusing data from multiple sensors or imaging types

• Experience deploying models to embedded hardware, including quantisation and/or distillation

• Eligible for UK SC clearance (UK citizen or 5+ years UK residency)

Benefits

We offer competitive compensation including;

• Share options vesting over three years
• Bupa private medical insurance
• 6% employer pension contribution
• 25 days leave plus bank holidays
• Enhanced mat/pat leave
• Enterprise level AI tooling
• Relocation support/home office budget