NVIDIA

1 week ago

Senior Platform AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Define and lead the architecture and delivery of an ML efficiency platform that powers NVIDIA’s intelligent automation ecosystem. Own end-to-end platform implementation and sustained production operations, including security, reliability, performance, orchestration patterns, auth, observability, and SLA enforcement. Set engineering standards across silicon architecture, build, methodology, validation, and applied AI teams, and mentor senior engineers while scaling job queues and storage/caching across heterogeneous compute environments.

Location: Santa Clara

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Define the architectural direction, infrastructure investments, and roadmap priorities for the efficiency platform across silicon architecture, build, methodology, validation, and applied AI teams.
•Define platform contracts and onboard new agents and skills from domain teams building on the platform.
•Own end-to-end platform delivery and sustained production operations, ensuring security, reliability, performance, and platform evolution.
•Lead unified solutions including orchestration patterns, authentication/authorization, observability, and SLA enforcement; scale storage and caching across heterogeneous compute environments.
•Serve as technical authority for AI-powered infrastructure across SCG by setting engineering standards, resolving cross-team architectural challenges, and mentoring senior engineers.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually

Equity and Bonus:Equity

Key Requirements

•8+ years designing and operating production-grade platform or backend infrastructure.
•5+ years of direct ML infrastructure experience, including end-to-end ownership of model serving platforms or latency-sensitive backend services.
•Track record setting technical direction at department or company level, including defining platform strategy and architectural standards across multiple teams.
•Strong Python skills and proficiency in at least one compiled language such as C, C++, Go, Java, or Rust.
•Hands-on experience with job queues and sandboxed execution (Kubernetes Jobs, Celery/Sidekiq/Temporal, and container runtimes with resource isolation).

Experience:ML infrastructureDistributed systemsBackend infrastructure

Education:Bachelor's

Skills:CommunicationLeadershipMentoringCross-team alignment

Tech Stack:PythonCC++GoJavaRustKubernetes JobsCelerySidekiqTemporalContainer runtimesAuthenticationAuthorizationObservabilitySLA enforcement

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

Loading job details...

Preparing the role view and application actions.

NVIDIA

1 week ago

Senior Platform AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Santa Clara

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Define the architectural direction, infrastructure investments, and roadmap priorities for the efficiency platform across silicon architecture, build, methodology, validation, and applied AI teams.
•Define platform contracts and onboard new agents and skills from domain teams building on the platform.
•Own end-to-end platform delivery and sustained production operations, ensuring security, reliability, performance, and platform evolution.
•Lead unified solutions including orchestration patterns, authentication/authorization, observability, and SLA enforcement; scale storage and caching across heterogeneous compute environments.
•Serve as technical authority for AI-powered infrastructure across SCG by setting engineering standards, resolving cross-team architectural challenges, and mentoring senior engineers.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually

Equity and Bonus:Equity

Key Requirements

•8+ years designing and operating production-grade platform or backend infrastructure.
•5+ years of direct ML infrastructure experience, including end-to-end ownership of model serving platforms or latency-sensitive backend services.
•Track record setting technical direction at department or company level, including defining platform strategy and architectural standards across multiple teams.
•Strong Python skills and proficiency in at least one compiled language such as C, C++, Go, Java, or Rust.
•Hands-on experience with job queues and sandboxed execution (Kubernetes Jobs, Celery/Sidekiq/Temporal, and container runtimes with resource isolation).

Experience:ML infrastructureDistributed systemsBackend infrastructure

Education:Bachelor's

Skills:CommunicationLeadershipMentoringCross-team alignment

Tech Stack:PythonCC++GoJavaRustKubernetes JobsCelerySidekiqTemporalContainer runtimesAuthenticationAuthorizationObservabilitySLA enforcement

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor