Machine Learning Engineer - #2095500

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