6 months ago
London, United KingdomSenior
Responsibilities
- Implement and scale training pipelines for large transformer and LLM models from data ingestion and preprocessing through distributed training and evaluation.
- Build and optimize low-latency, highly reliable inference services, including autoscaling, routing, and fallbacks.
- Tune GPU kernels, improve utilization, and identify performance bottlenecks across the training and inference stack.
- Collaborate with ML scientists to implement advanced training and inference methods and bring them to production.
- Participate in hiring, mentoring, and developing other engineers.
- Improve technical standards, reliability, and operational excellence across the AI platform.
Requirements
- At least 5 years of software engineering experience.
- Degree in Computer Science, Computer Engineering, or a related field, or equivalent experience with strong technical fundamentals.
- Hands-on experience with model training, model inference at scale, or low-level GPU programming such as CUDA or Triton.
- Deep knowledge of at least one programming language, such as Python, Ruby, Java, or Go.
- Experience working in production environments at meaningful traffic, data, or organizational scale.
- Clear technical communication and effective collaboration with engineers and non-engineers.
Benefits
- Competitive salary and equity, with regular compensation reviews.
- Weekday lunch, snacks, and a fully stocked kitchen.
- Unlimited access to Claude Code and other AI tools.
- Pension scheme with matching up to 4%.
- Life assurance plus comprehensive health and dental insurance for employees and dependents.
- Flexible paid time off.
- Paid maternity leave and six weeks of paternity leave.
- Cycle-to-Work Scheme and secure bike storage.
- MacBook standard equipment, with Windows available for certain roles.
- Hybrid working policy requiring at least three days per week in the office.
Tech Stack
Categories
About Intercom
Intercom builds a customer service platform that combines an AI agent (Fin), live chat, and a modern help desk to support sales and support teams. It sells its software as a SaaS subscription to businesses that want to manage customer conversations across web, mobile, and email with automation and analytics. Founded in 2011 and headquartered in San Francisco, the company is privately held and serves startups through large enterprises.