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Full-time
bachelor degree
Posted 17d ago
~40 hrs/week
Responsibilities
Design and deploy end-to-end AI solutions, including agents and copilots, to improve efficiency within ASIC networking product engineering. Unify fragmented engineering data into scalable pipelines to enable advanced analytics and automated workflows.
Requirements
Requires a Bachelor's degree in Computer Science or a related field and 8+ years of experience building production AI and data solutions. Must have hands-on expertise in Python, LLMs, RAG, and developing scalable data services.
Full job description
NVIDIA has transformed accelerated computing through innovation powered by exceptional technology and people. Within ASIC networking product engineering group, you will help bring AI into product engineering by turning fragmented engineering data into scalable, production-ready solutions for analysis, decision-making, and efficiency.
In this role, you will define and deliver AI solutions that unify data across NVIDIA infrastructure and engineering systems, enabling advanced analytics for production engineering teams through AI agents, copilots, and workflow automation. You will own solutions end to end, from architecture and development through deployment, maintenance, and continuous improvement, and help shape how ASIC networking product engineering uses AI to scale engineering productivity.
What you'll be doing:
Design, build, and maintain AI solutions that improve our division efficiency across production, characterization, analysis, and operational workflows.
Develop agentic analytics capabilities that enable engineers to query, analyze, and reason over ASIC data using AI agents and copilots.
Consolidate data from multiple infrastructure and engineering systems into scalable, reliable pipelines and reusable services.
Partner with production engineering teams to identify pain points, define high-value use cases, and deliver measurable impact.
Build and support tools for data access, automation, reporting, anomaly detection, and engineering insight generation.
Collaborate across NVIDIA to align interfaces, improve data quality, and support scalable deployment models.
Drive continuous improvement through user feedback, monitoring, and roadmap planning.
What we need to see:
Bachelor’s in Computer Science, Software Engineering, Data Science, or a related field, or equivalent experience.
8+ years of experience as an AI solutions engineer, machine learning engineer, or software engineer building production AI/data solutions.
Strong experience designing, developing, deploying, and maintaining end-to-end AI applications in production.
Hands-on expertise with Python and modern software engineering practices.
Practical experience with LLMs, AI agents, RAG, workflow orchestration, and data/analytics applications.
Strong background building data pipelines, APIs, services, and applications on top of structured and semi-structured engineering data.
Strong communication skills and a proactive, ownership-driven mindset.
Advantage: experience in semiconductor, hardware, product engineering, test, characterization, or manufacturing analytics environments.
Ways to stand out from the crowd:
Experience building AI solutions for engineering or manufacturing organizations.
Familiarity with agent frameworks, vector databases, telemetry platforms, or internal knowledge/data systems.
Background in cross-functional work spanning software, data, infrastructure, and product engineering.
Proven track record of introducing new technical capabilities and driving adoption across engineering teams.
Related keywords
AI AgentsCopilotsRAGLLMsPythonASICNetworkingData PipelinesVector DatabasesTelemetryMachine LearningSoftware EngineeringProduct EngineeringManufacturing AnalyticsWorkflow AutomationAnomaly Detection
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.
Offices: 2701 San Tomas Expressway, Santa Clara, CA 95050, US · No. 8, Ji Hu Rd., Taipei City, Taipei City 114, TW · Nanakramguda, Serilingampally Mandal, Plot # 6A&B, IT Park Layout, RR District, Hyderabad, Telangana 500046, IN · No. 127 Andheri Kurla Road, CNB Square, Mumbai, Village Chakala, Andheri East 400 093, IN · Survey No. 144/145, Samrat Ashok Path, Off Airport Road, Pune, Yerwada 411 006, IN
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.
Offices: 2701 San Tomas Expressway, Santa Clara, CA 95050, US · No. 8, Ji Hu Rd., Taipei City, Taipei City 114, TW · Nanakramguda, Serilingampally Mandal, Plot # 6A&B, IT Park Layout, RR District, Hyderabad, Telangana 500046, IN · No. 127 Andheri Kurla Road, CNB Square, Mumbai, Village Chakala, Andheri East 400 093, IN · Survey No. 144/145, Samrat Ashok Path, Off Airport Road, Pune, Yerwada 411 006, IN