3 months ago

AI Infrastructure Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 14 hours agoStatus: Live

Job Summary

Senior+ AI Infrastructure Engineer to design and operate training pipelines and low-latency inference services for large transformer/LLM models. Work on GPU-level performance, collaborate with ML scientists, contribute to production-scale AI infrastructure, and mentor peers while upholding high standards of reliability and operational excellence in Intercom’s AI platform.

Location: Berlin

Workplace: Hybrid

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Sr. Manager level

Key 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 inference services that deliver low-latency, high-reliability experiences, including autoscaling, routing, and fallbacks.
•Work on GPU-level performance: tuning kernels, improving utilization, and identifying bottlenecks across the training and inference stack.
•Collaborate closely with ML scientists to implement cutting edge training and inference methods and bring them to production.
•Play an active role in hiring, mentoring, and developing other engineers on the team.

Pay and Benefits

Equity and Bonus:Equity

Perks:Hybrid WorkingEquity

Key Requirements

•5+ years of experience in software engineering, with a track record of shipping high-quality products or platforms.
•Degree in Computer Science, Computer Engineering, or a related field (or equivalent experience with strong fundamentals).
•Hands-on experience with model training or model inference at scale, or low-level GPU work (CUDA or Triton kernels).
•Comfortable working in production environments at meaningful scale (traffic, data, or organizational).
•Deep knowledge of at least one programming language (e.g. Python, Ruby, Java, Go) and ability to write clean, reliable code.

Experience:5+ yearsAI/ML

Education:Bachelor's in Computer Science

Skills:PythonCUDATriton

Languages:English

Tech Stack:PythonCUDATritonKubernetesAWS

Company Brief

Intercom

Provides a customer messaging platform combining chat, bots, and product tours to help businesses convert, engage, and support customers across their lifecycle. Integrates with CRM and workflow tools for personalized in-app and email communication.

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: San Francisco, United States

Founded: 2011

Website LinkedIn

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Intercom

3 months ago

AI Infrastructure Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 14 hours agoStatus: Live

Job Summary

Location: Berlin

Workplace: Hybrid

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Sr. Manager level

Key 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 inference services that deliver low-latency, high-reliability experiences, including autoscaling, routing, and fallbacks.
•Work on GPU-level performance: tuning kernels, improving utilization, and identifying bottlenecks across the training and inference stack.
•Collaborate closely with ML scientists to implement cutting edge training and inference methods and bring them to production.
•Play an active role in hiring, mentoring, and developing other engineers on the team.

Pay and Benefits

Equity and Bonus:Equity

Perks:Hybrid WorkingEquity

Key Requirements

•5+ years of experience in software engineering, with a track record of shipping high-quality products or platforms.
•Degree in Computer Science, Computer Engineering, or a related field (or equivalent experience with strong fundamentals).
•Hands-on experience with model training or model inference at scale, or low-level GPU work (CUDA or Triton kernels).
•Comfortable working in production environments at meaningful scale (traffic, data, or organizational).
•Deep knowledge of at least one programming language (e.g. Python, Ruby, Java, Go) and ability to write clean, reliable code.

Experience:5+ yearsAI/ML

Education:Bachelor's in Computer Science

Skills:PythonCUDATriton

Languages:English

Tech Stack:PythonCUDATritonKubernetesAWS

Company Brief

Intercom

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: San Francisco, United States

Founded: 2011

Website LinkedIn