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Freelance Nvidia Machine Learning Jobs in New York

Nvidia

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

As a Senior Machine Learning Engineer at NVIDIA, you will build the machine learning brain that keeps NVIDIA's global DGX Cloud healthy, efficient and ready for the next waves of AI breakthroughs.

Paramount

Lead Machine Learning Engineer

Manhattan, NY · On-site

$112K - $148K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Senior Lead Machine Learning Engineer, Entry & Re-engagement 45724 Overview We are looking for a ... Nvidia Triton). * Mentorship: Experience mentoring junior engineers or leading technical ...

NOUS RESEARCH

Machine Learning Engineer

New York, NY · On-site

You'll work across training infrastructure, inference optimization, and reinforcement learning ... NVIDIA GPU programming (Triton, CUTLASS, custom CUDA kernels) and deep NCCL knowledge * FP8 or FP4 ...

Adaptive Security

Founding Machine Learning Engineer

New York, NY · On-site

$90K - $120K/yr

  • Medical

  • Retirement

  • PTO

About Adaptive NVIDIA and OpenAI's only AI cybersecurity investment. Adaptive is a cybersecurity startup on a mission to stop AI-powered cyberattacks. In December 2025, the company announced an $81M ...

Nvidia

HPC Middleware Developer

Holmdel, NJ · On-site

... machine learning, cloud computing, and system co-design. What you'll be doing: The team is ... NVIDIA is widely considered to be one of the technology world's most desirable companies to work ...

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Freelance Nvidia Machine Learning information

What are the key skills and qualifications needed to thrive as a freelance Nvidia machine learning specialist?

To thrive as a Freelance Nvidia Machine Learning Engineer, you need a strong background in machine learning principles, deep learning frameworks (such as TensorFlow or PyTorch), and proficiency in Python programming, often supported by a relevant degree or certifications. Familiarity with Nvidia hardware (GPUs), CUDA programming, and tools like Nvidia Deep Learning SDKs is essential for optimizing and deploying models efficiently. Exceptional problem-solving, self-management, and client communication skills help you deliver effective solutions and maintain successful freelance relationships. Mastery of these skills ensures you can build high-performance models, meet client expectations, and stay competitive in the rapidly evolving ML landscape.

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

AspectFreelance Nvidia Machine LearningFreelance Data Scientist
Required CredentialsKnowledge of Nvidia GPU architectures, CUDA programming, machine learning frameworksStatistics, programming, data analysis skills, often with similar certifications
Work EnvironmentProject-based, remote, often with tech companies or startupsProject-based or consulting, remote or on-site, across various industries
Industry UsageAI, deep learning, GPU-accelerated applicationsData analysis, predictive modeling, business insights

Freelance Nvidia Machine Learning specialists focus on GPU-accelerated AI projects using Nvidia technologies, while Freelance Data Scientists handle broader data analysis and modeling tasks. Both roles are in high demand for tech-driven projects but differ in technical focus and tools used.

What are some common challenges freelance Nvidia machine learning specialists face when working with clients remotely?

Freelance Nvidia Machine Learning specialists often encounter challenges such as ensuring compatibility between client hardware and Nvidia GPU requirements, effectively communicating technical needs and project progress to non-expert clients, and managing project timelines without in-person oversight. Additionally, freelancers may need to set up secure access to client data or cloud environments, which can require extra coordination. Proactively clarifying expectations, maintaining clear documentation, and staying current with Nvidia's latest tools (like CUDA, cuDNN, or TensorRT) are essential strategies for overcoming these challenges.

What does a freelance Nvidia machine learning specialist do?

A Freelance Nvidia Machine Learning specialist is an independent contractor who uses Nvidia hardware and software platforms, such as CUDA and TensorRT, to develop, optimize, and deploy machine learning models. These professionals often work with clients to accelerate AI workloads, implement deep learning solutions, and leverage GPU computing for data processing tasks. Their projects may include computer vision, natural language processing, or other AI applications that benefit from Nvidia’s technology stack. Freelancers in this field need strong programming skills, familiarity with Nvidia SDKs, and experience optimizing models for high-performance computing environments.
What are the most commonly searched types of Nvidia Machine Learning jobs in New York? The most popular types of Nvidia Machine Learning jobs in New York are:
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Freelance Nvidia Machine Learning jobs near you

Senior Machine Learning Engineer

Nvidia

New York, NY • On-site

$114K - $157K/yr

Full-time

Posted 9 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 243 rated software companies

Job description

As a Senior Machine Learning Engineer at NVIDIA, you will build the machine learning brain that keeps NVIDIA's global DGX Cloud healthy, efficient and ready for the next waves of AI breakthroughs. DGX Cloud fuses NVIDIA GPUs, NVLink networking and the full AI software stack into elastic infrastructure powering large language models, drug discovery, autonomous driving and climate science. Your models will turn billions of telemetry signals into predictive insight. This frees customers to innovate while our platform runs smarter.

What you'll be doing:

  • Ground breaking and developing innovative machine learning algorithms and models that propel our AI products.

  • Build production models for anomaly detection, predictive maintenance and usage optimization.

  • Develop tools surfacing real time telemetry, efficiency metrics and long term trends.

  • Develop forecasting and simulation models for global scale planning.

  • Analyzing complex datasets to determine the best approach for model training and optimization.

  • Translate findings into clear engineering actions with infrastructure, operations and product teams.

  • Participating in cross-functional projects to integrate machine learning capabilities into various NVIDIA products.

What we need to see:

  • Master's degree or PhD in Mathematics, Statistics, Machine Learning or related quantitative field (or equivalent experience).

  • 8+ years experience applying Machine Learning to operational systems.

  • Proven track record of building and deploying Machine Learning models in production environments.

  • Experience with time series analysis and optimization algorithms.

  • Familiarity with distributed systems and cloud platforms such as AWS and Kubernetes.

  • Strong software engineering skills and proficiency in Python.

  • Effective verbal/written communication, and technical presentation skills.

  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.

  • A track record of delivering high-impact projects to compete in a fast-paced environment.

Ways to stand out from the crowd:

  • Experience solving capacity planning problems.

  • Deep understanding of GPU performance metrics.

  • Familiarity with prometheus and PromQL.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 7, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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