AI Infrastructure Engineer

Responsibilities

We are representing a confidential AI technology company seeking a Senior AI Infrastructure Engineer to join their London team. In this role, you will:

• Implement and scale training pipelines for large transformer and LLM models, covering data ingestion, preprocessing, distributed training, and evaluation
• Build and optimize inference services that deliver low-latency, high-reliability experiences, including autoscaling, routing, and fallback mechanisms
• Work on GPU-level performance optimization: tuning kernels, improving utilization, and identifying bottlenecks across the training and inference stack
• Collaborate closely with ML scientists to implement cutting-edge training and inference methods and bring them to production
• Play an active role in hiring, mentoring, and developing other engineers on the team
• Raise the bar for technical standards, reliability, and operational excellence across the AI platform

What We're Looking For

Our talent team is seeking candidates with:

• 5+ years of experience in software engineering, with a strong track record of shipping high-quality products or platforms
• A degree in Computer Science, Computer Engineering, or a related field (or equivalent experience with very strong fundamentals)
• Hands-on experience with one or more of the following:
  • Model training (especially transformers and LLMs)
  • Model inference at scale (especially transformers and LLMs)
  • Low-level GPU work, such as writing CUDA or Triton kernels
• Comfort working in production environments at meaningful scale (traffic, data, or organizational)
• Strong communication skills and ability to explain complex technical topics to different audiences
• Pride in strong technical fundamentals, love of learning, and willingness to invest in your own development
• Deep knowledge of at least one programming language (Python, Ruby, Java, Go, etc.)

Bonus skills (not required):

• Experience at AI-native companies that train and/or run inference for their own models
• Experience running training or inference workloads on Kubernetes
• Experience with AWS or other major cloud providers
• Production experience with Python in ML or infrastructure contexts
• Demonstrated passion for technology through personal projects, open source contributions, or published content

How We Work With You

When you apply through Get A Job.ai, our recruiting team will review your background and conduct an initial screening. If there's a strong match, we will submit your profile to our client for consideration. Please do not contact the client directly—all communication will be coordinated through our team to ensure the best outcome for your candidacy.

This is a hybrid position based in London, with an expectation of at least three days per week in the office.

Pay

Compensation details will be discussed during the screening process and will be determined by factors including location, job level, skills, and experience.

Equal Employment Opportunity: Get A Job.ai is committed to inclusive recruiting practices. We evaluate all candidates based on qualifications and merit, without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, disability, veteran status, or other protected classifications.