SC Cleared Machine Learning Engineer

iO Associates; Bristol (VA); Hybrid; USD 87,014 - 120,482; Full time

Job summary

iO Associates in Bristol is seeking an ML Engineer specialized in computer vision to move models from experimental codebases to rugged, production-ready systems. You will develop solutions for object detection, tracking, and multi-spectral imaging in a defence context.

You’ll work on SLAM-based real-time mapping, edge-optimized pipelines, and productionizing research models. A hybrid role with on-site presence 2–3 days is offered, and you must have active UK SC clearance and British citizenship.

Qualifications

• Active SC clearance and British citizenship required.
• Defence or government project experience preferred.
• Strong Python and PyTorch background for computer vision.
• Experience deploying models to production and on edge devices.

Responsibilities

• Build, train, and deploy deep learning models for object detection, segmentation, and tracking.
• Implement SLAM for real-time mapping and localization on autonomous platforms.
• Optimize computer vision pipelines for edge devices and constrained hardware.
• Wrap research models into maintainable production code.

Skills

Python

PyTorch

SLAM

Edge computing

TensorRT

ONNX

Tools

Docker

CI/CD

Job description

Location: Bristol / Hybrid (2-3 days on-site)

Clearance Required: Active UK SC Clearance and British Citizen

The Role

We are supporting our client in the defence sector to build next-generation systems that process complex, real-world visual data in real time. We need an ML Engineer who specializes in computer vision to help move models from experimental codebases into rugged, production-ready systems.

You’ll be working with everything from object detection and tracking to multi-spectral imaging, deploying models that operate reliably in high-stakes environments.

What You’ll Do

Build & Optimize: Design, train, and deploy deep learning models for object detection, segmentation, and tracking.

Spatial Awareness: Implement and optimize SLAM algorithms to enable real-time mapping and localization for autonomous platforms.

Scale: Optimize computer vision pipelines to run efficiently on edge devices and constrained hardware.

Productionize: Wrap research-grade models into clean, maintainable, and scalable production code.

What We’re Looking For

Core Stack: Strong programming skills in Python and deep familiarity with PyTorch.

CV & Spatial Expertise: Hands‑on experience building computer vision models and working with SLAM (Simultaneous Localization and Mapping) frameworks.

Engineering Focus: Experience with Docker, CI/CD pipelines, and writing production‑grade code.

• Must have prior experience in Defence or Government related work.

You must hold active SC clearance and be a British citizen.

Nice to Have

Experience optimizing models for edge hardware (TensorRT, ONNX).

Familiarity with C++ for performance‑critical vision and SLAM pipelines.

Experience handling synthetic data generation or working with imperfect, low-resolution datasets.