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Ml Platform Jobs (NOW HIRING)

NVIDIA

Senior ML Platform Engineer

Durham, NC · On-site

$101K - $138K/yr

They are seeking a Senior ML Platform Engineer to architect, build, and scale high-performance ML infrastructure, ensuring reliable platforms for scientists and engineers to train and deploy advanced ...

New

NVIDIA

Senior ML Platform Engineer

Westford, MA · On-site

$108K - $149K/yr

They are seeking a Senior ML Platform Engineer to architect, build, and scale high-performance ML infrastructure, ensuring reliable platforms for scientists and engineers to train and deploy advanced ...

New

NVIDIA

Senior ML Platform Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

They are seeking a Senior ML Platform Engineer to architect, build, and scale high-performance ML infrastructure, ensuring reliable platforms for scientists and engineers to train and deploy advanced ...

New

Nvidia

Senior ML Platform Engineer

Boulder, CO

$108K - $148K/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

OR

$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

Santa Clara, CA · On-site

$122K - $168K/yr

They are seeking a Senior ML Platform Engineer to architect, build, and scale high-performance ML infrastructure, focusing on creating reliable, automated platforms for ML development.

New

NVIDIA

Senior ML Platform Engineer

Boulder, CO · On-site

$110K - $151K/yr

They are seeking a Senior ML Platform Engineer to architect, build, and scale high-performance ML infrastructure, ensuring reliable platforms for scientists and engineers to train and deploy advanced ...

NVIDIA

Senior ML Platform Engineer

Santa Clara, CA

$121K - $167K/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 ...

New

Nvidia

Senior ML Platform Engineer

Santa Clara, CA

$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 ...

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All JobsMl Platform Jobs

Ml Platform information

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$33

$63

$94

How much do ml platform jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for ml platform 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 is an ML Platform?

An ML (Machine Learning) Platform is a comprehensive infrastructure or set of tools that supports the end-to-end lifecycle of machine learning projects. It typically provides features for data preparation, model training, experiment tracking, deployment, and monitoring of machine learning models. ML Platforms help streamline workflows, improve collaboration among data scientists and engineers, and enable scalable and reproducible machine learning development. Popular examples include Google AI Platform, AWS SageMaker, and Azure Machine Learning.

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 strong programming skills (especially in Python), a solid understanding of machine learning concepts, and experience with cloud infrastructure, often supported by a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Kubernetes, Docker, and cloud platforms such as AWS or GCP, as well as knowledge of CI/CD systems, is typically required. Excellent problem-solving abilities, collaboration, and effective communication are vital soft skills for working across data science, engineering, and product teams. These skills ensure scalable, reliable, and efficient deployment of machine learning models, driving impactful business solutions.

What are some common challenges faced by professionals working on an ML Platform team, and how can they be addressed?

Professionals on an ML Platform team often encounter challenges such as ensuring scalability for diverse model workloads, maintaining cross-team communication, and supporting a variety of frameworks and tools. Addressing these requires strong collaboration with data scientists, software engineers, and infrastructure teams to understand their needs and pain points. Implementing clear documentation, robust monitoring, and automation can also help streamline workflows and reduce bottlenecks, making the platform more reliable and user-friendly.

What is the difference between Ml Platform vs Data Scientist?

AspectML PlatformData Scientist
Required credentialsTypically requires knowledge of cloud services, programming, and ML toolsRequires degrees in data science, statistics, or related fields, with programming skills
Work environmentPrimarily cloud-based, working with ML tools and deployment pipelinesMostly office-based, analyzing data, building models, and interpreting results
Employer and industry usageUsed by tech companies, startups, and enterprises deploying ML solutionsEmployed across industries for data analysis, modeling, and insights

ML Platform professionals focus on deploying, managing, and scaling machine learning models using cloud and software tools. Data Scientists analyze data, develop models, and interpret results. While both roles work with machine learning, ML Platform specialists handle infrastructure and deployment, whereas Data Scientists focus on data analysis and model development.

More about Ml Platform jobs
What job categories do people searching Ml Platform jobs look for? The top searched job categories for Ml Platform jobs are:
Ml Platform jobs near you
Infographic showing various Ml Platform job openings in the United States as of May 2026, with employment types broken down into 59% Full Time, and 41% Part Time. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $133,026 per year, or $64 per hour.

AI/ML Platform Engineer

Surge InfoTech LLC

Alexandria, VA • On-site

Full-time

Posted 9 days ago

Job description

  • /No C2C option/

    • We are seeking a hands-on Senior AI/ML Platform Engineer with 10+ years of IT experience and a strong track record of building, deploying, and operationalizing AI/ML systems. The ideal candidate is a doer who excels in implementing scalable, production-grade AI/ML solutions across cloud environments.

    Core Requirements
  • 10+ years of IT/engineering experience
  • 3+ years of handson AI/ML development experience
  • 4+ years working directly with AWS services (Lambda, EC2, S3, DynamoDB, IoT Core, API Gateway, Fargate/ECS)
  • Proven experience deploying ML systems into production environments
  • Strong coding skills and ability to build systems endtoend
    • Key Skills
  • Deep Learning frameworks: TensorFlow, PyTorch, Keras
  • LLMs, prompt engineering, NLP pipelines
  • Python and Java as primary languages; strong engineering fundamentals
  • FastAPI and microservices for ML inference
  • InfrastructureasCode (Terraform)
  • Kubernetes and Docker for scalable ML workloads
  • Distributed/cloud systems design with AWS
  • Edgetocloud system integration experience
  • Handson build experience (not just design/architecture)
    • Responsibilities
  • Build and deploy productiongrade ML/AI pipelines and services
  • Develop LLMpowered and NLPdriven applications
  • Write, optimize, and maintain highquality Pythonbased ML code
  • Implement scalable infrastructure using Terraform, AWS, and Kubernetes
  • Build FastAPIbased inference services and cloud APIs
  • Collaborate with crossfunctional engineering teams to deliver highimpact systems
  • Troubleshoot, optimize, and own systems endtoend as a handson engineer
    • Preferred Skills
  • Experience with distributed systems and microservices
  • Strong understanding of ML model lifecycle, deployment patterns, and operational monitoring

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