Platform engineer, MLOps

Overview

As a Platform engineer, MLOps, you will be critical to deploying and managing cutting-edge infrastructure for AI/ML operations. You will collaborate with AI/ML engineers and researchers to develop a robust CI/CD pipeline that supports safe and reproducible experiments. Your responsibilities also include setting up and maintaining monitoring, logging, and alerting systems to oversee training runs and client-facing APIs. You will ensure training environments are available and efficiently managed across multiple clusters, and you will enhance our containerization and orchestration systems with tools such as Docker and Kubernetes.

Responsibilities

• Work closely with AI/ML engineers and researchers to design and deploy a CI/CD pipeline that ensures safe and reproducible experiments.
• Set up and manage monitoring, logging, and alerting systems for extensive training runs and client-facing APIs.
• Ensure training environments are consistently available across multiple clusters.
• Develop and manage containerization and orchestration systems using Docker and Kubernetes.
• Operate and oversee large Kubernetes clusters with GPU workloads.
• Improve reliability, quality, and time-to-market of our software solutions.
• Measure and optimize system performance to anticipate customer needs and drive continual improvement.
• Provide primary operational support and engineering for multiple large-scale distributed software applications.

Qualifications

• You have professional experience with:
  • Model training
  • Huggingface Transformers
  • PyTorch
  • vLLM
  • TensorRT
  • Infrastructure as code tools like Terraform
  • Scripting languages such as Python or Bash
  • Cloud platforms such as Google Cloud, AWS or Azure
  • Git and GitHub workflows
  • Tracing and Monitoring
• Familiar with high-performance, large-scale ML systems
• You have a knack for troubleshooting complex systems and enjoy solving challenging problems
• Proactive in identifying problems, performance bottlenecks, and areas for improvement
• Take pride in building and operating scalable, reliable, secure systems
• Comfortable with ambiguity and rapid change

Preferred skills and experience

• Familiar with monitoring tools such as Prometheus, Grafana, or similar
• 5+ years building core infrastructure
• Experience running inference clusters at scale
• Experience operating orchestration systems such as Kubernetes at scale

Benefits

• Generous PTO, plus company holidays
• Comprehensive medical and dental insurance
• Paid parental leave for all parents (12 weeks)
• Fertility and family planning support
• Early-detection cancer testing through Galleri
• Competitive pension scheme and company contribution
• Annual work-life stipends for home office setup, cell phone, internet
• Wellness stipend for gym, massage/chiropractor, personal training, etc.
• Learning and development stipend
• Company-wide off-sites and team off-sites
• Competitive compensation and company stock options

Details

• Seniority level: Mid-Senior level
• Employment type: Full-time
• Job function: Engineering and Information Technology
• Industries: Software Development

London, United Kingdom

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