1 month ago

Inference Optimization Manager

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Lead the Performance Labs team building Modular Cloud’s optimization platform for LLM inference. Own the technical direction from GPU kernels through inference engine and distributed systems, turning customer workloads into a continuous optimization loop. Partner with GTM, Product, and Engineering to deliver highly customized inference performance for agentic use cases, grow the team, and share external thought leadership through technical blog posts.

Location: United States, Canada

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Manager level

Key Responsibilities

•Lead the team building the optimization platform for LLM inference on Modular Cloud across GPU and ASIC architectures.
•Own Modular Cloud’s technical direction to deliver and sustain state-of-the-art inference performance for agentic use cases.
•Partner with GTM to deliver customized LLM inference tuned to customer workloads and guide cross-stack optimizations from kernels to cloud infrastructure.
•Grow and develop the team by setting priorities and enabling engineers to tackle hard performance problems.
•Champion the team externally by publishing blog posts on LLM inference optimization approaches and best practices.

Travel: Low travel

Pay and Benefits

Salary: USD 234,000 - 286,000 annually

Equity and Bonus:Equity

Perks:Health Insurance401kPaid Leave

Key Requirements

•5+ years in distributed systems or performance engineering, including experience leading or managing engineering teams.
•Ship durable, reusable software tools and libraries adopted across teams, and guide a team to do the same.
•Evaluate technical tradeoffs and set priorities with strong communication and technical leadership.
•Translate ambiguous customer and product needs into focused engineering direction.
•Demonstrate creativity, curiosity, collaboration, and alignment with team culture.

Experience:AI infrastructureLLMDistributed systemsPerformance engineering

Skills:Technical leadershipCommunicationPrioritizationProblem-solvingCollaboration

Tech Stack:LLMGPUASICDistributed systemsKubernetesCloud nativeInference engine

Company Brief

Modular

Provides infrastructure and developer tools to build, deploy, and scale large AI models and foundation-model applications, including model hosting, orchestration, and SDKs to accelerate AI product development.

Industry: AI & Machine Learning

Website

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Modular

1 month ago

Inference Optimization Manager

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: United States, Canada

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Manager level

Key Responsibilities

•Lead the team building the optimization platform for LLM inference on Modular Cloud across GPU and ASIC architectures.
•Own Modular Cloud’s technical direction to deliver and sustain state-of-the-art inference performance for agentic use cases.
•Partner with GTM to deliver customized LLM inference tuned to customer workloads and guide cross-stack optimizations from kernels to cloud infrastructure.
•Grow and develop the team by setting priorities and enabling engineers to tackle hard performance problems.
•Champion the team externally by publishing blog posts on LLM inference optimization approaches and best practices.

Travel: Low travel

Pay and Benefits

Salary: USD 234,000 - 286,000 annually

Equity and Bonus:Equity

Perks:Health Insurance401kPaid Leave

Key Requirements

•5+ years in distributed systems or performance engineering, including experience leading or managing engineering teams.
•Ship durable, reusable software tools and libraries adopted across teams, and guide a team to do the same.
•Evaluate technical tradeoffs and set priorities with strong communication and technical leadership.
•Translate ambiguous customer and product needs into focused engineering direction.
•Demonstrate creativity, curiosity, collaboration, and alignment with team culture.

Experience:AI infrastructureLLMDistributed systemsPerformance engineering

Skills:Technical leadershipCommunicationPrioritizationProblem-solvingCollaboration

Tech Stack:LLMGPUASICDistributed systemsKubernetesCloud nativeInference engine

Company Brief

Modular

Industry: AI & Machine Learning

Website