Senior AI Infra Engineer — Scale Training & Inference

Intercom; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Job summary

Fin, now part of Salesforce, is building the future of AI-powered customer experiences and is hiring a Senior+ AI Infrastructure Engineer.

You will join a small, highly technical AI Infra team, developing training pipelines and inference services for transformer/LLM models, with a focus on GPU-level performance and production-scale reliability. The role emphasizes collaboration, mentoring, and raising engineering standards.

Qualifications

• 5+ years of experience in software engineering and shipping high-quality products.
• Degree in Computer Science, Computer Engineering, or related field (or equivalent).
• Hands-on experience with model training or model inference at scale (transformers/LLMs) and/or low-level GPU work (CUDA/Triton).
• Comfortable in production environments at meaningful scale.
• Strong communication and ability to explain technical topics to diverse audiences.
• Proficient in at least one programming language (Python, Ruby, Java, Go, etc.).

Responsibilities

• Implement and scale training pipelines for large transformer/LLM models from data ingestion to distributed training and evaluation.
• Build and optimize inference services with low latency, high reliability, autoscaling, routing and fallbacks.
• Tune GPU kernels and improve utilization across training and inference stacks.
• Collaborate with ML scientists to implement cutting-edge training/inference methods and bring them to production.
• Mentor and develop other engineers on the team; raise technical standards and operational excellence.

Skills

Model training

Model inference

GPU programming

Python

CUDA

Triton

Communication

Education

Bachelor's degree in Computer Science/Engineering or related field

Tools

CUDA

Triton

Job description

Fin, now part of Salesforce, is building the future of AI-powered customer experiences and is hiring a Senior+ AI Infrastructure Engineer.

You will join a small, highly technical AI Infra team, developing training pipelines and inference services for transformer/LLM models, with a focus on GPU-level performance and production-scale reliability. The role emphasizes collaboration, mentoring, and raising engineering standards.