MLOps Team Lead - Build Scalable AI Infrastructure

Fundamental; United Kingdom; On-site; GBP 120,000 - 190,000; Full time

Benefits offered by this job

Competitive equity package

Relocation support

Comprehensive health coverage

Job summary

Fundamental is an AI research lab redefining enterprise decision-making. As Lead MLOps Engineer you will mentor a team, own the MLOps roadmap, and build scalable pipelines and deployments across training and inference.

You’ll partner with Research, Engineering and Product to align infrastructure with strategic goals. Ideal candidates have 7+ years in MLOps (5+ in leadership), strong Python and Bash/Go skills, and hands-on experience with MLflow, TorchServe/TensorFlow Serving, Kubernetes on

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 7+ years of experience in MLOps, with 5+ years in a technical leadership role
• Strong software engineering skills in Python, with Bash and/or Go
• Proven track record of building and leading high-performing MLOps or infrastructure teams
• Experience building and designing MLOps infrastructure from the ground up
• Deep experience with MLOps platforms (MLflow, WandB, etc.) and frameworks (PyTorch, TensorFlow, etc.)
• Deep experience with model serving frameworks (Triton, TorchServe, TensorFlow Serving, KServe) for high scalability and low latency inference
• Experience building and managing data pipelines to support both model training and inference
• Good experience with Kubernetes on a major cloud provider (AWS, GCP, or Azure) and with infrastructure as code (Terraform, Helm, GitOps)
• Proficient with observability and monitoring tools (Prometheus, Grafana, Datadog, OpenTelemetry)
• Excellent communication skills with ability to translate between research and production contexts

Responsibilities

• Lead and mentor a team of MLOps engineers
• Define and drive the MLOps roadmap
• Establish best practices, standards, and processes for ML infrastructure
• Own technical decision-making for ML infrastructure architecture and tooling
• Architect and oversee scalable ML pipelines, CI/CD workflows, and orchestration
• Collaborate on serving infrastructure strategy ensuring training-side decisions don’t hinder downstream
• Collaborate on inference architecture with training context
• Design and maintain feature stores and scalable data pipelines
• Bridge research and production between experimentation and deployment
• Define logging, alerting, and monitoring strategy for model performance and reliability

Skills

MLOps leadership

Python

Bash/Go

ML infrastructure

Model serving frameworks

Kubernetes on cloud

IaC (Terraform/Helm)

Observability/monitoring

Science-to-prod translation

Education

Bachelor's or Master's in CS/Engineering

Tools

Kubernetes

Terraform

MLflow

WandB

TorchServe/TensorFlow Serving

Triton

Job description

Fundamental is an AI research lab redefining enterprise decision-making. As Lead MLOps Engineer you will mentor a team, own the MLOps roadmap, and build scalable pipelines and deployments across training and inference.

You’ll partner with Research, Engineering and Product to align infrastructure with strategic goals. Ideal candidates have 7+ years in MLOps (5+ in leadership), strong Python and Bash/Go skills, and hands-on experience with MLflow, TorchServe/TensorFlow Serving, Kubernetes on