AI Operations Engineer – Finance at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Finance, Artificial Intelligence, TechnologyIndustries

Requirements

5+ years of experience in AI-adjacent areas (ML ops, NLP, or related roles), with at least 2 years applying gen AI to business problems
BS/MS or equivalent experience in Data Science, Computer Science, Information Systems, Software Engineering, Economics, or other technical fields (Technical Master’s with corp/ops finance or business background preferred)
Experience working with production AI applications, including monitoring, tracing, logging, performance evaluation, and data flywheels
Hands-on expertise in model evaluation frameworks, including LLM-as-a-judge and human-in-the-loop review workflows
Excellent communication to work with business partners, IT, internal development teams, and senior management

Responsibilities

Leverage AI, automation, and business knowledge to systematically assess bot & agent answer quality, flagging potentially incorrect or incomplete answers for human review
Create robust evaluation data sets and data flywheels based on finance feedback, business priorities, and knowledge bases
Monitor & optimize AI systems using observability stacks to track model performance, system health, and lifecycle metrics
Build continuous evaluation pipelines to measure production model outputs, accuracy, and confidence distributions

Skills

Key technologies and capabilities for this role

MLOpsNLPGenerative AIObservabilityModel EvaluationAI AgentsData PipelinesContinuous EvaluationModel Monitoring

Questions & Answers

Common questions about this position

What experience level is required for this AI Operations Engineer role?

The role requires 5+ years of experience in AI-adjacent areas such as ML ops or NLP, with at least 2 years applying generative AI to business problems.

What education is needed for this position?

A BS/MS or equivalent experience in Data Science, Computer Science, Information Systems, Software Engineering, Economics, or other technical fields is required; a technical Master’s with corporate/ops finance or business background is preferred.

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

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What skills will help me stand out as a candidate?

Subject matter expertise in corporate finance, GenAI expertise including prompt optimization and RAG pipelines, experience with multi-agentic systems, and implementing secure authentication systems will make 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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