Role at a glance
- Salary
- $272K – $431.3K/yr
- Location
- 2 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 10+ overall years building and delivering production software systems, including 5+ years leading engineering teams as a manager
- Education
- A degree in Computer Science, Computer Engineering, or a related field (BS or MS) or equivalent experience.
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Role Summary
The Senior Engineering Manager will lead and scale the NVIDIA Inference Microservices (NIM) Factory team, which delivers day-0 model launches and enterprise-grade software for reliable, performant, and secure AI services. The role partners with product, research, SRE, and security to define strategy, execute across workstreams, and maintain the platform’s technical health.
What You'll Do
- Lead the NIM Factory engineering team across containers, orchestration, workflow, observability, and platform APIs.
- Define the vision, strategy, and roadmap for building, shipping, and operating NIM from day-0 launch through enterprise-grade hardening.
- Own end-to-end delivery of cross-functional programs, align stakeholders, and manage dependencies.
- Drive predictable delivery across multiple programs by managing priorities, resourcing, schedules, and dependencies.
- Establish engineering excellence through code health and reviews, documentation, CI/CD, and testing.
- Collaborate with research and platform teams on inference architecture and scalable deployment patterns.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required: 10+ years building and delivering production software systems, including 5+ years managing engineering teams; experience with complex cross-functional programs; cloud-native engineering with containers, Kubernetes, and microservices; CI/CD, testing, and observability; Python; hiring, coaching, and developing senior engineers or tech leads; communication and stakeholder management; and a degree in Computer Science, Computer Engineering, or a related field (BS or MS), or equivalent experience.
Required
- 10+ overall years building and delivering production software systems
- 5+ years leading engineering teams as a manager
- Driving complex, cross-functional programs from inception to successful production launch and scale
- Cloud-native engineering with containers, Kubernetes, and microservices
- Modern SDLC practices including CI/CD, testing, and observability
- Proficiency with Python
- Hiring, coaching, and developing senior engineers or tech leads
- Communication and stakeholder management across product, research, security, and operations
Preferred
- Experience leading multiple teams or managing managers
- Large-scale LLM inference or model-serving platforms including Triton, TensorRT-LLM, or vLLM in production
- Architecting next-generation container build systems or CI/CD platforms at scale
- Building organizations across multiple time zones
- Building talent pipelines and mentoring managers or tech leads
- Contributions to open-source ecosystems, technical publications, or talks in containers, Kubernetes, GPU, or inference communities
Original job description
Content provided by the employer
Original job description
Content provided by the employer
NVIDIA is the platform upon which every new AI‑powered application is built! We are seeking a deeply technical, hands‑on Senior Engineering Manager to lead the NVIDIA Inference Microservices (NIM) Factory team. You will lead and scale a world‑class engineering organization that delivers day‑0 model launches and follows through with enterprise‑grade software—to delight customers with reliable, performant, and secure AI services at massive scale. You will partner closely with product, research, SRE, and security to define strategy, drive execution across multiple workstreams, and safeguard the long‑term technical health of the platform.
What you'll be doing:
Lead the NIM Factory engineering team (containers, orchestration, workflow, observability, platform APIs); attract, hire, onboard, and grow top talent.
Define vision, strategy, and roadmap for how we build, ship, and operate NIM from day‑0 launch through enterprise‑grade hardening (security, reliability, performance, compliance).
Own end‑to‑end delivery of cross‑functional programs; align stakeholders and manage dependencies.
Drive predictable delivery across multiple programs; manage priorities, resourcing, schedules, and dependencies
Establish engineering excellence: code health and reviews, documentation, CI/CD, testing.
Collaborate with research and platform teams on inference architecture and scalable deployment patterns.
What we need to see:
10+ overall years building and delivering production software systems, including 5+ years leading engineering teams as a manager; experience leading multiple teams or managing managers is a plus.
Proven track record driving complex, cross‑functional programs from inception to successful production launch and scale.
Strong foundation in cloud‑native engineering (containers, Kubernetes, microservices) and modern SDLC practices (CI/CD, testing, observability).
Proficiency with cloud languages such as Python; ability to read code, guide designs, and drive high‑quality engineering outcomes.
Demonstrated ability to hire, coach, and develop senior engineers/tech leads; build inclusive teams and a culture of ownership and excellence.
Excellent communication and stakeholder management; ability to influence across product, research, security, and operations.
A degree in Computer Science, Computer Engineering, or a related field (BS or MS) or equivalent experience.
Ways to stand out from the crowd:
Led teams that built and operated large‑scale LLM inference or model‑serving platforms (Triton, TensorRT‑LLM, vLLM) in production.
Experience architecting next-generation container build systems or CI/CD platforms at scale.
Built organizations across multiple time zones; established durable engineering processes that improved quality and velocity.
Proven success building talent pipelines, mentoring managers/tech leads, and increasing team engagement and retention.
Contributions to open‑source ecosystems, technical publications, or talks in containers, Kubernetes, GPU, or inference communities.
We are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward‑thinking and creative people in the world working for us. If you're creative and autonomous with a real passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.