Senior ML Engineer - Edge AI Performance & Deployment

United States Digital Space LLC; Greater London; On-site; GBP 90,000 - 125,000; Full time

Job summary

the company is seeking a Senior Machine Learning Engineer to own end-to-end model releases for on-vehicle deployments, partnering with inference and performance teams to ensure production-ready systems that meet strict runtime constraints.

You will take models from training to deployment, applying practical optimisation techniques and maintaining tight feedback loops with stakeholders across the stack.

Qualifications

• Proven experience improving performance in production systems with tight constraints (latency, memory, bandwidth, power/thermal, or cost).
• Strong hands-on experience training and iterating on deep learning models in PyTorch (not just using high-level tooling).
• Strong proficiency with at least one relevant stack/toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL) and confidence learning adjacent frameworks quickly.
• Comfort operating at multiple levels of abstraction — from high-level model behaviour down to low-level kernel/runtime execution.
• Familiarity with model optimisation concepts such as quantisation and/or distillation.

Responsibilities

• Own end-to-end delivery of model releases, from initial requirements through training, evaluation, iteration, and final readiness for deployment.
• Train and iterate on PyTorch models with a strong experimental approach (hypothesis-driven iteration, ablations, clear evaluation criteria).
• Debug and improve model performance using strong analytical skills—identifying regressions, root-causing issues, and proposing fixes.
• Apply optimisation techniques (quantisation and distillation) where beneficial, understanding trade-offs and when methods are appropriate.
• Collaborate cross-functionally with adjacent ML and performance engineering teams to hand off models and align on optimisation priorities.
• Communicate clearly with stakeholders to align on delivery timelines, trade-offs, and readiness criteria.

Skills

PyTorch

Model optimization

TensorRT

CUDA

QNN (Qualcomm)

Triton

OpenCL

Tools

TensorRT

OpenCL

Job description

the company is seeking a Senior Machine Learning Engineer to own end-to-end model releases for on-vehicle deployments, partnering with inference and performance teams to ensure production-ready systems that meet strict runtime constraints.

You will take models from training to deployment, applying practical optimisation techniques and maintaining tight feedback loops with stakeholders across the stack.