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Ml Platform Engineer Jobs (NOW HIRING)

Nvidia

Senior ML Platform Engineer

Durham, NC

$101K - $138K/yr

We are now looking for a ML Platform Engineer to help accelerate the next era of machine learning innovation. In this role, you will architect, build, and scale our high-performance ML infrastructure ...

Nvidia

Senior ML Platform Engineer

Santa Clara, CA ยท On-site

$122K - $168K/yr

We are now looking for a ML Platform Engineer to help accelerate the next era of machine learning innovation. In this role, you will architect, build, and scale our high-performance ML infrastructure ...

Nvidia

$104K - $143K/yr

We are now looking for a ML Platform Engineer to help accelerate the next era of machine learning innovation. In this role, you will architect, build, and scale our high-performance ML infrastructure ...

Nvidia

Senior ML Platform Engineer

Westford, MA

$108K - $149K/yr

We are now looking for a ML Platform Engineer to help accelerate the next era of machine learning innovation. In this role, you will architect, build, and scale our high-performance ML infrastructure ...

CEI

Senior ML Platform Engineer

Kissimmee, FL

$70 - $80/hr

Senior ML Platform Engineer Job at a Glance * Title: Senior ML Platform Engineer * Location: Orlando, FL * Contract: W2 only, 12-month contract with potential for extension or full-time conversion

Toyota

Senior AI/ML Platform Engineer

Plano, TX

$100K - $137K/yr

As a Senior AI/ML Platform Engineer, you will design, build, and support scalable platform capabilities that enable enterprise MLOps and LLMOps. You will work independently on features and services ...

Guidewire Software

Senior AI/ML Platform Engineer

San Mateo, CA ยท On-site

$119K - $163K/yr

We thrive on curiosity, continuous improvement, and a culture that values diverse perspectives and teamwork. ยน As a Senior AI/ML Platform Engineer, you will architect and scale the ML platform for ...

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Ml Platform Engineer information

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How much do ml platform engineer jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for ml platform engineer in the United States is $63.95, according to ZipRecruiter salary data. Most workers in this role earn between $50.48 and $73.80 per hour, depending on experience, location, and employer.

What are ML Platform Engineers?

ML Platform Engineers are specialized software engineers who design, build, and maintain the infrastructure and tools needed to support the development, deployment, and scaling of machine learning models. They bridge the gap between data science and production engineering by automating model training, monitoring, versioning, and serving. Their work enables data scientists to focus on modeling while ensuring that ML solutions are reliable, reproducible, and scalable in real-world environments.

What is the difference between Ml Platform Engineer vs Data Scientist?

AspectML Platform EngineerData Scientist
Required credentialsBachelor's/Master's in CS, Engineering, or related; experience with cloud platformsBachelor's/Master's in Statistics, Math, or CS; strong programming skills
Work environmentBuilds and maintains ML infrastructure, collaborates with engineering teamsAnalyzes data, develops models, and interprets results
Industry usageTech companies, AI startups, enterprises deploying ML systemsResearch institutions, tech firms, data-driven organizations

ML Platform Engineers focus on developing and maintaining the infrastructure that supports machine learning models, while Data Scientists primarily analyze data and build models. Both roles often collaborate but serve different functions within the AI and data ecosystem.

How does an ML Platform Engineer typically collaborate with data scientists and software engineers within a company?

ML Platform Engineers work closely with both data scientists and software engineers to streamline the process of developing, deploying, and maintaining machine learning models. They provide the infrastructure and tools necessary for data scientists to build and experiment with models efficiently, while ensuring seamless integration with production systems managed by software engineers. Regular communication, participation in cross-functional meetings, and shared project management tools are common ways teams collaborate. This close collaboration helps to bridge the gap between research and production, ensuring robust, scalable, and reliable ML solutions.

What are the key skills and qualifications needed to thrive as an ML Platform Engineer, and why are they important?

To thrive as an ML Platform Engineer, you need a strong background in computer science, software engineering, and machine learning concepts, often supported by a degree in a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), containerization (Docker, Kubernetes), CI/CD pipelines, and knowledge of ML frameworks (TensorFlow, PyTorch) are commonly required. Collaboration, problem-solving, and strong communication skills help you work efficiently with data scientists, engineers, and stakeholders. These skills ensure the development, scalability, and reliability of robust ML infrastructure that empowers teams to deploy and manage models effectively.
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Ml Platform Engineer jobs near you
Infographic showing various Ml Platform Engineer job openings in the United States as of June 2026, with employment types broken down into 60% Full Time, 37% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $133,026 per year, or $64 per hour.
Senior ML Platform Engineer

Senior ML Platform Engineer

Nvidia

Durham, NC

$101K - $138K/yr

Full-time

Posted 8 days ago

Job description

NVIDIA is at the forefront of innovations in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention-the GPU-functions as the visual cortex of modern computing and is central to groundbreaking applications from generative AI to autonomous vehicles. We are now looking for a ML Platform Engineer to help accelerate the next era of machine learning innovation.

In this role, you will architect, build, and scale our high-performance ML infrastructure using modern Infrastructure-as-Code practices. Your primary focus will be on creating reliable, automated platforms that empower scientists and engineers to train and deploy the most advanced ML models on some of the world's most powerful GPU systems. Join our top team and apply your SRE and software engineering skills to craft robust, user-friendly platforms for seamless ML development.

What You'll Be Doing:

  • Design, build, and maintain our core ML platform infrastructure as code, primarily using Ansible and Terraform, ensuring reproducibility and scalability across large-scale, distributed GPU clusters.

  • Apply SRE principles to diagnose, troubleshoot, and resolve complex system issues across the entire stack, ensuring high availability and performance for critical AI workloads.

  • Develop robust internal automation and tooling for ML workflow orchestration, resource scheduling, and platform operations, with a strong focus on software engineering best practices.

  • Collaborate with ML researchers and applied scientists to understand infrastructure needs and build solutions that streamline their end-to-end experimentation.

  • Evolve and operate our multi-cloud and hybrid (on-prem + cloud) environments, implementing monitoring, alerting, and incident response protocols.

  • Participate in on-call rotation to provide support for platform services and infrastructure running critical ML jobs, driving root cause analysis and implementing preventative measures.

  • Write high-quality, maintainable code (Python, Go) to contribute to the core orchestration platform and automate manual processes.

  • Drive the adoption of modern GPU technologies and ensure smooth integration of next-generation hardware into ML pipelines (e.g., GB200, NVLink, etc.).

What We Need To See:

  • BS/MS in Computer Science, Engineering, or equivalent experience.

  • 5+ years in software/platform engineering or SRE roles, including 3+ years focused on ML infrastructure or distributed compute systems.

  • Strong proficiency in Infrastructure-as-Code (IaC) tools, specifically Ansible and Terraform, with a proven track record of building and managing production infrastructure.

  • SRE-oriented mindset with extensive experience in diagnosing system-level issues, performance tuning, and ensuring platform reliability.

  • Solid understanding of ML workflows and lifecycle-from data preprocessing to deployment.

  • Proficiency in operating containerized workloads with Kubernetes and Docker.

  • Strong software engineering skills in languages such as Python or Go, with a focus on automation, tooling, and writing production-grade code.

  • Experience with Linux systems internals, networking, and performance tuning at scale.

Ways To Stand Out From The Crowd:

  • Experience building or operating ML platforms supporting frameworks like PyTorch or TensorFlow at scale.

  • Deep understanding of distributed training techniques (e.g., data/model parallelism, Horovod, NCCL).

  • Expertise with modern CI/CD methodologies and GitOps practices.

  • Passion for building developer-centric platforms with great UX and strong operational reliability.

  • Proven ability to contribute code to complex orchestration or automation platforms.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 9, 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.
Nvidia logo

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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