Machine Learning Engineer

Position: Staff Machine Learning Engineer
Metric has partnered with a VC-backed retail AI company building large-scale ML systems that power product discovery across search, ads, and e-commerce platforms. Their technology transforms product data using LLMs and computer vision to drive relevance, performance, and measurable commercial impact at global scale.

They are seeking a Staff Machine Learning Engineer to build and scale the ML systems powering their platforms in production.

What you’ll work on:

Architecting and evolving Kubernetes-native ML platforms supporting hundreds of production models

Designing high-throughput inference and training systems for LLMs and retrieval-augmented generation

Building and standardising ML services and APIs to accelerate experimentation and deployment

Developing robust observability, monitoring, and reliability practices for ML systems in production

Partnering closely with ML engineers and product teams to unblock delivery and raise technical standards

What they’re looking for:

7+ years' industry experience in Machine Learning Engineering

Proven experience serving ML workloads at scale in production

Strong background with Kubernetes, Docker, cloud platforms (AWS, GCP, Azure)

Experience designing and maintaining ML and data pipelines

Hands-on exposure to LLMs, vector databases, and modern AI stacks

Track record of optimising systems for cost, throughput, and latency

Strong Python skills with PyTorch experience

High engineering bar around code quality, testing, and CI/CD

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