ZipRecruiter

Log In

2

Full Time Nvidia Machine Learning Jobs (NOW HIRING)

Nvidia

Senior Deep Learning Software Engineer

Santa Clara, CA · Hybrid

$143K - $189K/yr

Familiarity with NVIDIA's deep learning SDKs such as TensorRT. * Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.

Nvidia

Senior Deep Learning Software Engineer

Redmond, WA · Hybrid

$137K - $180K/yr

Familiarity with NVIDIA's deep learning SDKs such as TensorRT. * Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.

Jane Street

Machine Learning Engineer

New York, NY · On-site

You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ... Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading ...

Quantiphi, Inc.

Senior Machine Learning Engineer

$125K - $165K/yr

Industry Verticals (Telco, BFSI, HCLS etc.) and is an established Elite/Premier Partner of NVIDIA ... Role: Senior Machine Learning Engineer Experience Level: 3-6+ yrs Work Location: Dallas, TX Role ...

Quantiphi, Inc.

Senior Machine Learning Engineer

$125K - $165K/yr

Industry Verticals (Telco, BFSI, HCLS etc.) and is an established Elite/Premier Partner of NVIDIA ... Role: Senior Machine Learning Engineer Experience Level: 3-6+ yrs Work Location: Dallas, TX Role ...

next page

Showing results 1-20

All JobsNvidia Machine Learning JobsFull Time Nvidia Machine Learning Jobs

Full Time Nvidia Machine Learning information

See salary details

$13

$26

$48

How much do full time nvidia machine learning jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for full time nvidia machine learning in the United States is $26.35, according to ZipRecruiter salary data. Most workers in this role earn between $21.39 and $27.88 per hour, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers or AI research scientists at top technology companies can earn $500,000 or more annually, especially with bonuses and stock options. These roles typically require advanced degrees, extensive experience, and expertise in deep learning, neural networks, and high-performance computing environments.

What is the difference between Full Time Nvidia Machine Learning vs Data Scientist?

AspectFull Time Nvidia Machine LearningData Scientist
Required CredentialsBachelor's or higher in CS, AI, or related fields; experience with Nvidia toolsBachelor's or higher in CS, Statistics, or related fields; data analysis skills
Work EnvironmentTech companies, AI research labs, Nvidia-specific projectsVarious industries including tech, finance, healthcare
Employer & Industry UsagePrimarily Nvidia, tech giants, AI startupsBroad industry use, including tech, finance, consulting

Full Time Nvidia Machine Learning roles focus on developing AI models using Nvidia's hardware and software, often requiring specialized knowledge of Nvidia tools. Data Scientists analyze data to extract insights across industries. While both roles involve data and AI, Nvidia Machine Learning positions are more hardware and software-specific, whereas Data Scientists have broader data analysis responsibilities.

How much do NVIDIA machine learning engineers make?

NVIDIA machine learning engineers typically earn a salary ranging from $100,000 to $160,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in deep learning and GPU programming can earn higher compensation, often supplemented with bonuses and stock options.

Which 5 jobs will survive AI?

Full Time Nvidia Machine Learning roles are likely to persist as they involve developing and maintaining AI models, which require specialized expertise in deep learning, programming, and hardware optimization. Jobs in AI research, data science, software engineering, AI hardware engineering, and technical product management are expected to remain in demand due to their complexity and the need for human oversight. These roles often require advanced skills, certifications, and continuous learning to adapt to evolving AI technologies.

How difficult is it to get hired at NVIDIA?

Getting hired for a full-time machine learning role at NVIDIA can be competitive, often requiring strong technical skills in deep learning, programming (such as Python and CUDA), and relevant experience or advanced degrees. The hiring process typically involves multiple interview rounds assessing technical knowledge, problem-solving ability, and cultural fit.
What are the most commonly searched types of Nvidia Machine Learning jobs? The most popular types of Nvidia Machine Learning jobs are:
What states have the most Full Time Nvidia Machine Learning jobs? States with the most job openings for Full Time Nvidia Machine Learning jobs include:
Full Time Nvidia Machine Learning jobs near you
Infographic showing various Full Time Nvidia Machine Learning job openings in the United States as of July 2026, with employment types broken down into 74% Full Time, 24% Part Time, and 2% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $54,803 per year, or $26.3 per hour.
Machine Learning Engineer, AI Safety & Security - Supporting NVIDIA - Santa Clara (Hybrid)

Machine Learning Engineer, AI Safety & Security - Supporting NVIDIA - Santa Clara (Hybrid)

Sustainable Talent

Remote

$60.25 - $80.25/hr

Full-time

Posted 13 days ago

Job description

Job Summary:
Sustainable Talent is partnering with Nvidia, a global leader in computer graphics and accelerated computing. They are seeking a Machine Learning Engineer to focus on AI Safety for LLMs, working alongside NVIDIA’s research and engineering teams to assess and improve the safety and inclusivity of LLM models.
Responsibilities:
• Develop datasets and moderator models for evaluating LLM models and end-to-end systems for Content Safety, ML Fairness. These LLM models can be txt-to-txt or multimodal-to-txt.
• Develop datasets for training LLM models with SFT and RL techniques, for Content Safety, ML Fairness, Security and more.
• Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems.
• Define and track key metrics for responsible LLM behavior and usage.
• Follow the best practices of automation, monitoring, scale, safety.
• Contribute to our repositories and develop safety tools to help ML teams be more effective.
• Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets.
• Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance.
• Collaborate with multidisciplinary teams: Collaborate with product engineers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.
Qualifications:
Required:
• Bachelor’s or Master’s Degree in Computer Science or related field or equivalent experience.
• 2+ years of work experience as a Machine Learning Engineer or Deep Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions.
• Strong programming skills in languages such as Python. Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.
• Proficiency in data manipulation, analysis, and visualization using tools like NumPy and pandas.
• Deep understanding of machine learning algorithms, statistical models, and data structures.
• Familiarity with software development practices and version control systems (e.g., Git).
• Good at problem solving and analytical ability.
• Excellent collaboration and communication skills.
Preferred:
• Experience with GenAI Security including Prompt Injection Stability, Model Extraction, Confidentiality/Data Extraction, Integrity, Availability and Adversarial Robustness.
• Experience with one or more of the following areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application.
• Experience with alignment/fine-tuning of LLMs - including regular LLMs as well as VLMs (Vision Language Model) or any-to-text
• Experience with multimodal and/or multilingual Content Safety, legal and regulatory compliance.
• Passion for AI and a demonstrated commitment to advancing the field through innovative research, prior scientific research and publication experience.
Company:
Sustainable Talent provides staffing, consulting and outsourcing services. Founded in 2009, the company is headquartered in Wayne, USA, with a team of 201-500 employees. The company is currently Growth Stage.

Apply