ML Ops Lead
London, United Kingdom
GBP 84K-120K (estimate) Senior-level Full Time
Tasks
- Architect maintain optimize MLOps pipelines
- Automate provisioning using Infrastructure as Code
- Build scale secure ML and generative AI platforms
- Define infrastructure roadmap for AI and ML workloads
- Deploy LLMs to production
- Enforce data governance platform security and compliance
- Ensure high availability low latency model serving
- Establish FinOps frameworks
- Implement CI CD frameworks for model deployment
- Implement autoscaling spot and downscaling policies
- Improve unit economics for training and serving
- Lead DevOps team
- Monitor model drift and data pipelines
- Provide incident response
- Set up telemetry and observability metrics
- Track allocate forecast AI infrastructure spend
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Ansible | Auto Scaling | Azure | Bash | CI/CD | Cloudability | Data Governance | Docker | GCP | GitHub Actions | Go | Hugging Face | Hugging Face TGI | Hugging Face Transformers | Incident Management | Inference Server | Infrastructure as Code | Jenkins | Kubecost | Kubeflow | Kubernetes | Kubernetes networking | LLM-Ops | Langsmith | ML Ops | MLflow | Observability | Python | Security Compliance | Service Mesh | Spot instances | Telemetry | Terraform | Triton Inference | Triton Inference Server | VLLM | “as-code”
Education
N/A
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