Machine Learning Engineer

Senior AI Platform Engineer (MLOps / ML Infrastructure)

Location: Bristol (On-Site)

Job Type: Full-Time, Permanent

Salary: Dependent on Experience (DOE)

The Opportunity

Our client is building next-generation intelligent robotic systems and is seeking a Senior AI Platform Engineer to own and scale the machine learning infrastructure that powers training, deployment and continuous improvement of advanced AI capabilities.

This role sits at the intersection of cloud infrastructure, machine learning operations, data engineering and robotics, offering a unique opportunity to shape how advanced AI systems are developed and deployed at scale.

The Role

You'll be responsible for building the infrastructure and workflows that connect data collection, training, evaluation, deployment and fleet management into a seamless platform.

Working closely with AI researchers and robotics engineers, you'll transform complex machine learning workflows into scalable, production-ready systems.

Key Responsibilities

Build and maintain scalable ML infrastructure

Develop containerised training environments

Manage cloud GPU orchestration and distributed training

Implement experiment tracking and model registries

Build automated data processing pipelines

Develop model evaluation and deployment workflows

Improve developer experience for ML teams

Extend CI/CD with ML-specific validation and testing

Automate infrastructure provisioning and deployment

Requirements

Degree in Computer Science, Software Engineering or related discipline

3+ years building cloud, platform, ML or data infrastructure

Strong Python development skills

Experience with training pipelines and distributed workloads

Docker and containerisation expertise

Experience with cloud platforms (GCP preferred)

Infrastructure-as-Code experience (Terraform preferred)

Desirable Experience

MLOps for robotics, autonomous systems or embodied AI

Kubeflow, SkyPilot or similar tooling

ONNX and TensorRT deployment

MLflow or experiment tracking platforms

Event-driven architectures

GPU orchestration and optimisation

Simulation and sim-to-real workflows

What's on Offer

Salary dependent on experience

Equity opportunities

Private healthcare

Conference and training budget

Opportunity to build infrastructure powering advanced AI and robotics systems

Collaborative and highly technical engineering culture