5 months ago
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 with autoscaling, routing, and fallbacks.
- Tune GPU kernels, improve utilization, and identify bottlenecks across the training and inference stack.
- Collaborate with ML scientists to implement 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
- 5+ years of software engineering experience.
- Degree in Computer Science, Computer Engineering, or a related field, or equivalent experience with very strong fundamentals.
- Hands-on experience with model training, model inference at scale, or low-level GPU work such as CUDA or Triton kernels.
- Experience working in production environments at meaningful traffic, data, or organizational scale.
- Deep knowledge of at least one programming language, such as Python, Ruby, Java, or Go.
- Strong communication, collaboration, technical fundamentals, and willingness to invest in professional development.
- Experience at AI-native companies, running workloads on Kubernetes, AWS or other major cloud providers, and production Python in ML or infrastructure contexts are preferred but not required.
Benefits
- Unlimited access to Claude Code and other AI tools.
- Generous paid time off above the statutory minimum.
- Hybrid work arrangement with at least three days per week in the office.
- MacBook standard equipment, with Windows available for certain roles.
- Fun events for employees, friends, and family.
Tech Stack
Categories
About Intercom
We’re Intercom — the AI customer service company helping businesses deliver incredible customer experiences at scale. Our platform combines Fin, the #1 AI Agent for customer service, with our next-generation Helpdesk, a modern workspace that gives support teams the power, speed and intelligence they need.