Senior MLOps Engineer
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Job Description
Senior MLOps Engineer ensuring data scientists have infrastructure and deployment strategies for AI models. Working remotely in the UK for a leading human data infrastructure company.
Responsibilities:
- Design and maintain scalable cloud environments (GCP/AWS) using Terraform.
- Manage GPU/TPU resource allocation for training, fine-tuning, and interactive notebooks.
- Build internal services and CLI tools to streamline the developer experience for the AI team.
- Design CI/CD/CT (Continuous Training) pipelines using tools such as GitHub Actions, MLFlow, Vertex AI Pipelines.
- Develop reusable patterns for model serving and manage service deployments to Kubernetes.
- Manage and optimize vector databases and embedding pipelines for RAG-based systems.
- Implement techniques to reduce latency and increase throughput.
- Solve scaling bottlenecks for serverless or containerized model deployments.
- Optimize GPU utilization and cloud spend without compromising performance.
- Monitor for model drift, data skew, and resource utilization.
- Implement LLM Tracing to monitor prompts, agent actions and general service health.
Requirements:
- 5+ years experience with cloud infrastructure and infrastructure as code.
- Previous experience with the ML and LLM lifecycle - training, hosting, optimisation, observability.
- Used to working closely with researchers and data scientists - taking experiments from worksheets into production.
- Strong grasp of ML fundamentals and modern GenAI stack.
Benefits:
- Competitive salary
- Remote working
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