AI Infrastructure Engineer

In this role you will help build and scale Intercom’s AI infrastructure, enabling fast training and reliable inference for large transformer and LLM models. You will work with a small, highly technical team to push the performance and reliability of our AI platform, powering Fin and the Intercom Customer Service Suite. You’ll collaborate with ML scientists to bring cutting-edge training and inference methods into production and mentor other engineers. This is a hands-on, impact-driven role at the core of our AI strategy.

• Competitive salary and equity
• Lunch and snacks
• Performance reviews
• Access to Claude Code and AI tools
• Pension scheme with 4% match
• Health and dental insurance for you and dependents

• Implement and scale training pipelines for large transformer and LLM models from data ingestion to distributed training and evaluation
• Build and optimize low-latency, reliable inference services with autoscaling, routing, and fallbacks
• Tune GPU kernels, improve utilization, and identify bottlenecks across training and inference stacks
• Collaborate with ML scientists to productionize advanced training and inference methods
• Mentor and develop other engineers on the team and elevate technical standards and reliability across the AI platform

• 5+ years of software engineering with a track record of shipping high-quality products or platforms
• Degree in Computer Science, Computer Engineering, or related field (or equivalent experience)
• Hands-on experience with model training (transformers/LLMs) or model inference at scale
• Experience with low-level GPU work (CUDA, Triton)
• Production experience at meaningful scale and strong communication skills
• Proficiency with at least one programming language (Python, Ruby, Java, Go, etc.)

• Clear communication
• Collaborative mindset
• Continuous learner
• Model training with transformers/LLMs
• Model inference at scale
• GPU programming (CUDA, Triton)