Model-as-a-Service Tech Lead at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Autonomous Driving, TechnologyIndustries

Requirements

Minimum 12+ years of hands-on experience developing and deploying scalable full-stack web services in a cloud environment
Proven Tech Lead or equivalent experience

Responsibilities

Serve as the primary, high-impact contributor on complex features, dedicating significant time to producing production code across the full stack, including UI, APIs, services, and infrastructure
Lead the code review process, setting and implementing thorough coding standards, performance benchmarks, and architectural integrity to ensure all merged code is high-quality, maintainable, and robust
Define and own the long-term technical roadmap, architecture, and design, ensuring deployment pipelines and services are platform-agnostic and easily deployable across the broader NVIDIA ecosystem, avoiding internal infrastructure dependencies
Lead the strategic implementation of web services and efficient batch processing queues to seamlessly integrate and operationalize foundation models into the customer-facing platform
Implement and ensure standards for production-grade performance, monitoring, and fault tolerance across all services, proactively identifying and resolving systemic technical debt and scalability bottlenecks
Take ultimate ownership of the CI/CD pipelines, container orchestration strategy (Kubernetes/Helm), and operational readiness, ensuring seamless scalability and reliability in production
Mentor and guide the engineering team on advanced practices in full-stack development, distributed systems design, performance optimization, and clean, portable code architecture
Act as the key technical liaison, translating complex requirements from Product Managers, ML Engineers, and Data Scientists into robust, portable, and implementable designs
Drive the technical vision, architecture, and implementation for a scalable, web-based platform enabling users to configure autonomous driving scenarios and generate synthetic data at scale
Design the entire platform for maximum portability and broad adoption across the NVIDIA ecosystem, championing web and batch processing patterns for foundation models

Skills

Full-Stack Development

Web Development

UI Development

Cloud Computing

Batch Processing

Platform Architecture

Synthetic Data Generation

Autonomous Driving

GPU Computing

Code Quality

Mentoring

Deployment Pipelines

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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