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Ml Platform Jobs (NOW HIRING)

ML Platform Engineer

Burbank, CA ยท On-site

$120 - $180/hr

Design and implement our greenfield ML platform 10Xing the Data Science team's impact * Work closely with Data Scientists to understand their development needs * Work closely with Stakeholders to ...

About the team The ML Platform team at Avride builds the infrastructure that powers large-scale ML training and data processing for autonomous driving. We sit between Cloud Platform and ML engineers ...

About the Role As an ML Platform Engineer at Stitch Fix, you will play a key role in building and maintaining the critical infrastructure that powers machine learning and AI across our organization.

About the team The ML Platform team at Avride builds the infrastructure that powers large-scale ML training and data processing for autonomous driving. We sit between Cloud Platform and ML engineers ...

ML Platform Engineer

San Mateo, CA ยท On-site

$124K - $210K/yr

Summary As an ML Platform Engineer, you'll help build and evolve the infrastructure that enables machine learning teams to develop, deploy, and operate models efficiently at scale. You'll work ...

ML Platform Engineer

San Mateo, CA ยท On-site

$124K - $210K/yr

Summary As an ML Platform Engineer, you'll help build and evolve the infrastructure that enables machine learning teams to develop, deploy, and operate models efficiently at scale. You'll work ...

ML Platform Engineer

$136K - $167K/yr

About the Role As an ML Platform Engineer at Stitch Fix, you will play a key role in building and maintaining the critical infrastructure that powers machine learning and AI across our organization.

LRS Consulting Services is seeking an AI/ML Platform Architect for an exciting contract to hire opportunity with our client. Lead the design, architecture, and implementation of an AI/ML platform ...

ML Platform Engineer

Santa Monica, CA ยท On-site

$170 - $300/hr

The Role This is an ML infrastructure role at the core of Hadrian's technology stack. While Data Science, Operations Research, Vision, and Document AI teams build models, you will own the platform ...

ML Platform Engineer

Los Angeles, CA ยท On-site

$170 - $300/hr

The Role This is an ML infrastructure role at the core of Hadrian's technology stack. While Data Science, Operations Research, Vision, and Document AI teams build models, you will own the platform ...

ML Platform Engineer

Los Angeles, CA ยท On-site

$170 - $300/hr

The Role This is an ML infrastructure role at the core of Hadrian's technology stack. While Data Science, Operations Research, Vision, and Document AI teams build models, you will own the platform ...

ML Platform Engineer

Los Angeles, CA ยท On-site

$170K - $300K/yr

The Role This is an ML infrastructure role at the core of Hadrian's technology stack. While Data Science, Operations Research, Vision, and Document AI teams build models, you will own the platform ...

* /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 ...

AI/ML Platform Architect

Lawrence, KS ยท On-site

$180 - $220/hr

Scion Technology has been engaged to conduct a search for an experienced AI/ML Platform Architect for our client, a rapidly growing cybersecurity company building AI-driven solutions for enterprise ...

Software Engineer, ML Platform

Denver, CO ยท On-site

$160 - $240/hr

As a Machine Learning Platform Engineer, you will work closely with AI/ML engineers to rapidly build, deploy, and iterate high-quality ML/AI infrastructure solutions at scale, ensuring both ...

Software Engineer, ML Platform

Denver, CO ยท On-site +1

$190K - $240K/yr

As a Machine Learning Platform Engineer, you will work closely with AI/ML engineers to rapidly build, deploy, and iterate high-quality ML/AI infrastructure solutions at scale, ensuring both ...

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ML Platform information

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$33

$63

$94

How much do ml platform jobs pay per hour?

As of Aug 23, 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
Infographic showing various Ml Platform job openings in the United States as of August 2026, with employment types broken down into 51% Full Time, 46% Part Time, and 3% Contract. Highlights an 78% Physical, 2% Hybrid, and 20% Remote job distribution, with an average salary of $133,026 per year, or $64 per hour.

ML Platform Engineer

Jobtailor

Burbank, CA โ€ข On-site

$120 - $180/hr

Other

Posted 5 days ago


Job description

Responsibilities
  • Design and implement our greenfield ML platform 10Xing the Data Science teamโ€™s impact
  • Work closely with Data Scientists to understand their development needs
  • Work closely with Stakeholders to understand the business problems driving model deployments and how models can augment their workflows
  • Assess and integrate cuttingโ€‘edge software and practices in Data Science and MLOps.
  • Refactor disjointed data science scripts and workflows into modular 'skills'
Requirements
  • 3+ years experience in Data Science and ML Engineering.
  • Deep experience developing as a team in Python
  • Deep experience designing and implementing MLOps platforms in a cloud environment
  • Deep experience implementing CI/CD workflows that manage model deployments
  • Experience developing containerized applications
  • Ability to innovate without over-engineering
  • Familiarity with wellโ€‘known statistical and ML models and methods
  • Strong detail orientation with a penchant for deployment reliability
  • Must successfully pass a background check
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