Anthropic

5 months ago

Technical Program Manager, Inference Performance

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 12 hours agoStatus: Live

Job Summary

Bridge inference systems and the broader organization by driving cross-functional initiatives across inference runtime and accelerator performance. Coordinate model launches, cross-platform dependencies, and reliability across multiple hardware targets to keep infrastructure teams shipping while Research, Product, and Safety depend on their output.

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Program & Project Management (PMO)

Seniority: Manager level

Key Responsibilities

•Systems Integration & Coordination: Lead cross-functional initiatives for new infrastructure integration, establishing ownership, timelines, and communication channels between teams; drive end-to-end planning for major infrastructure transitions including platform modernization and new tech adoption.
•Performance & Efficiency: Partner with engineering teams to identify optimization opportunities, track performance metrics, and prioritize work that unlocks capacity gains; coordinate across runtime and accelerator layers to ensure efficiency wins ship without compromising reliability.
•Launch Coordination: Drive end-to-end readiness for model and feature launches across multiple hardware platforms; establish processes for cross-platform validation, manage launch timelines, and ensure smooth handoffs between runtime, accelerator, and downstream teams.
•Strategic Planning: Own and prioritize the inference deployment roadmap, working with engineering leadership to prioritize initiatives and manage dependencies.
•Stakeholder Communication: Build strong relationships across research, engineering, and product teams to translate technical complexities into clear updates for leadership and ensure alignment on priorities and timelines.”],
•travelIfAny_or_otherNotes
•travel normalize
•travel
•travel
•travel

Key Requirements

•Have several years of experience in technical program management, with proven success delivering complex infrastructure programs, preferably in ML/AI systems or large-scale distributed systems
•Have deep technical understanding of inference systems, compilers, or hardware accelerators to engage substantively with engineers and identify technical risks
•Excel at creating structure and processes in ambiguous environments, bringing clarity to complex cross-team initiatives
•Have strong stakeholder management skills and can build trust with both technical and non-technical partners
•Are comfortable navigating competing priorities and using data to drive technical decisions

Experience:Ml/aiDistributed systems

Education:Bachelor's

Skills:LeadershipCommunicationProblem-solvingStakeholder managementPrioritization

Languages:English

Tech Stack:Inference systemsCompilersHardware acceleratorsDistributed systemsModel deployment

Eligibility

Work Authorization:Sponsorship available.

Company Brief

Anthropic

Develops large-scale AI systems and safety research to create reliable, steerable, and interpretable AI assistants and models for commercial and research applications.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2021

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

Anthropic

5 months ago

Technical Program Manager, Inference Performance

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 12 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Program & Project Management (PMO)

Seniority: Manager level

Key Responsibilities

•Systems Integration & Coordination: Lead cross-functional initiatives for new infrastructure integration, establishing ownership, timelines, and communication channels between teams; drive end-to-end planning for major infrastructure transitions including platform modernization and new tech adoption.
•Performance & Efficiency: Partner with engineering teams to identify optimization opportunities, track performance metrics, and prioritize work that unlocks capacity gains; coordinate across runtime and accelerator layers to ensure efficiency wins ship without compromising reliability.
•Launch Coordination: Drive end-to-end readiness for model and feature launches across multiple hardware platforms; establish processes for cross-platform validation, manage launch timelines, and ensure smooth handoffs between runtime, accelerator, and downstream teams.
•Strategic Planning: Own and prioritize the inference deployment roadmap, working with engineering leadership to prioritize initiatives and manage dependencies.
•Stakeholder Communication: Build strong relationships across research, engineering, and product teams to translate technical complexities into clear updates for leadership and ensure alignment on priorities and timelines.”],
•travelIfAny_or_otherNotes
•travel normalize
•travel
•travel
•travel

Key Requirements

•Have several years of experience in technical program management, with proven success delivering complex infrastructure programs, preferably in ML/AI systems or large-scale distributed systems
•Have deep technical understanding of inference systems, compilers, or hardware accelerators to engage substantively with engineers and identify technical risks
•Excel at creating structure and processes in ambiguous environments, bringing clarity to complex cross-team initiatives
•Have strong stakeholder management skills and can build trust with both technical and non-technical partners
•Are comfortable navigating competing priorities and using data to drive technical decisions

Experience:Ml/aiDistributed systems

Education:Bachelor's

Skills:LeadershipCommunicationProblem-solvingStakeholder managementPrioritization

Languages:English

Tech Stack:Inference systemsCompilersHardware acceleratorsDistributed systemsModel deployment

Eligibility

Work Authorization:Sponsorship available.

Company Brief

Anthropic

Develops large-scale AI systems and safety research to create reliable, steerable, and interpretable AI assistants and models for commercial and research applications.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2021

Website LinkedIn