We're looking for Senior+ AI Infrastructure Engineers to build the systems that train and serve Intercom's next generation of AI products.
\nIntercom is an AI company that builds from the GPU all the way up to a user agent that resolves millions of customer service queries a month. You'll join a small, highly technical team working at the cutting edge of modern AI infrastructure.
\nThe AI Infra team built the training pipelines and runs the inference for custom models like Fin Apex, which outperforms frontier models in customer service tasks, and is the foundation of the AI Group's full stack approach to AI.
\nAs a Senior AI Infrastructure Engineer focused on model training and inference, you will:
\nImplement and scale training pipelines for large transformer and LLM models, from data ingestion and preprocessing through distributed training and evaluation.
\nBuild and optimize inference services that deliver low-latency, high-reliability experiences for our customers, including autoscaling, routing, and fallbacks.
\nWork on GPU-level performance: tuning kernels, improving utilization, and identifying bottlenecks across our training and inference stack.
\nCollaborate closely with ML scientists to implement cutting edge training and inference methods and bring them to production.
\nPlay an active role in hiring, mentoring, and developing other engineers on the team.
\nRaise the bar for technical standards, reliability, and operational excellence across Intercom’s AI platform.
\nWe’re looking to hire Senior+ AI Infrastructure Engineers. You’re likely a great fit if:
\nYou have 5+ years of experience in software engineering, with a strong track record of shipping high-quality products or platforms.
\nYou hold a degree in Computer Science, Computer Engineering, or a related field (or you have equivalent experience with very strong fundamentals).
\nYou have hands-on experience with one or more of the following:
\nModel training (especially transformers and LLMs).
\nModel inference at scale (again, especially transformers and LLMs).
\nLow-level GPU work, such as writing CUDA or Triton kernels.
\nYou communicate clearly, can explain complex technical topics to different audiences, and enjoy close collaboration with both engineers and non-engineers.
\nYou take pride in strong technical fundamentals, love learning, and are willing to invest in your own development.
\nHave deep knowledge of at least one programming language (for example Python, Ruby, Java, Go, etc.).
\nExperience at AI native companies that train and/or run inference for their own models (e.g. modern AI labs or AI-native product companies).
\nExperience running training or inference workloads on Kubernetes.
\nExperience with AWS or other major cloud providers.
\nProduction experience with Python in ML or infrastructure contexts.
\nDemonstrated passion for technology through personal projects, open source, meetups, or publishing content about your work and learnings
\nXML job scraping automation by YubHub
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\nWhile this role is backend focused, you'll work across the entire product with our frontend, product, and design teams. Our full TypeScript stack is built on modern technologies including React, Node.js, PostgreSQL, Redis, and cutting-edge AI models.
\nOur team has a strong in-office culture and works in person 4–5 days per week in San Francisco. We love working together to stay creative and connected, with flexibility to work from home when focus matters most.
\nResponsibilities
\nWhat You'll Bring
\nCompensation Range
\nThe base salary for this full-time position, which spans multiple internal levels depending on qualifications, ranges between $180K - $275K plus benefits & equity.
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