AI Infrastructure Engineer

Requirements

• A track record of working on model training or model inference at scale, or on low-level GPU coding (e.g. CUDA, Triton). Experience with one is great, multiple is even better.
• 5+ years of experience in software engineering, with a strong track record of shipping high-quality products or platforms.
• Hold 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.
• Comfortable working in production environments at meaningful scale (traffic, data, or organizational).
• Communicate clearly, explain complex technical topics, and enjoy collaboration with engineers and non-engineers.
• Pride in strong technical fundamentals, love learning, and willingness to invest in personal development.

Nice to Haves

• 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, meetups, or content publication.

What You'll Be Doing

• Implementing and scaling training pipelines for large transformer and LLM models.
• Building and optimizing inference services for low-latency, high-reliability experiences.
• Working on GPU-level performance, tuning kernels, improving utilization, and identifying bottlenecks.
• Collaborating with ML scientists to implement cutting-edge methods and bring them to production.
• Playing an active role in hiring, mentoring, and developing other engineers on the team.
• Raising the bar for technical standards, reliability, and operational excellence across Intercom’s AI platform.

Perks and Benefits

• Competitive salary, annual bonus, and equity.
• Regular compensation reviews.
• Unlimited access to Claude Code and best-in-class AI tools.
• Generous paid time off above statutory minimum.
• Hybrid working.
• Option for MacBooks or Windows based on role requirements.
• Fun events for employees, friends, and family.