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Machine Learning Engineer – Computer Vision
PLASTIC RECYCLING LIMITED. Design, train, evaluate and deploy machine learning models onto a large fleet of operational vehicles .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing, training, and deploying machine learning models, particularly in computer vision applications for navigation and perception. Proficient in optimizing models for edge computing and integrating them with flight control systems.
Highest-signal resume keywords
Deep Neural Network TrainingPython ProgrammingModel Deployment on Embedded HardwareVisual Navigation and SLAMData Fusion from Multiple Sensors
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning Model DesignComputer VisionModel EvaluationModel OptimizationDeep Learning FrameworksObject DetectionImage Data ProcessingQuantizationDistillationFlight Data Analysis
Tools & Technologies
PyTorchEdge ComputingAnnotation PipelinesSimulation ToolsFlight Control Systems
Certifications & Qualifications
UK SC Clearance Eligibility
Industry Keywords
Visual OdometryGuidance and Control ConceptsOperational Performance MonitoringDataset CollectionHybrid Work Environment
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Design, train, evaluate and deploy machine learning models onto a large fleet of operational vehicles
- Build and improve models for vision-based navigation, perception and guidance
- Design, collect and 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 flight control engineers so model outputs feed reliably into guidance
- Diagnose failure modes from flight data and fix them through data or model changes
- Operate across dataset collection/design, model selection/training, edge inference optimisation, flight testing on real systems, and operational performance monitoring/improvement
Requirements
What you’ll need- 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
- 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
Comp & perks- 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