Senior AI Systems Engineer at NVIDIA

Tel Aviv-Yafo, TA, Israel

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Not SpecifiedCompensation

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

Full TimeJob Type

UnknownVisa

Semiconductor, Artificial IntelligenceIndustries

Requirements

BS/MS in CS/EE (or equivalent) with strong CS fundamentals
5+ years production Python; solid software engineering (APIs, testing, CI/CD)
Proven agentic LLM workflow experience (tool/function calling, orchestration, guardrails)
Classical ML fundamentals (supervised/unsupervised, feature engineering, evaluation)
RAG/IR familiarity (embeddings, vector stores, evaluation)
Data & infra: SQL/NoSQL and ETL over logs/metrics
Ownership and collaborative delivery across teams

Responsibilities

Develop systems for a broad range of applications, from data collection and analysis to MCP servers and agentic workflows over in-house orchestration APIs
Use NVIDIA's cloud compute to research and deploy resources needed for those systems
Participate in critical decisions about which technologies to employ
Assume senior duties in mentoring, code review, and instruction initiatives for the entire team

Skills

Key technologies and capabilities for this role

PythonAPIstestingCI/CDLLMtool callingorchestrationguardrailsMLfeature engineeringRAGembeddingsvector storesSQLNoSQLETL

Questions & Answers

Common questions about this position

What are the required qualifications for the Senior AI Systems Engineer role?

Candidates need a BS/MS in CS/EE (or equivalent) with strong CS fundamentals, 5+ years production Python experience with solid software engineering practices like APIs, testing, and CI/CD, proven agentic LLM workflow experience, classical ML fundamentals, RAG/IR familiarity, and skills in SQL/NoSQL, ETL, plus ownership and collaborative delivery.

What is the salary or compensation for this position?

This information is not specified in the job description.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What is the company culture like for this team at NVIDIA?

The team emphasizes innovation and a startup mentality balanced with quality and maintainability standards, rewarding valuable ideas from all members with time and creative freedom.

What experience will make me stand out as a candidate?

Knowledge of VLSI/EDA software methodologies and computing environments, strong foundation in data structures and algorithms, in-depth understanding of how LLMs work, and experience with distributed systems, CI/CD, K8s, and/or Git will help you stand out.

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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