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Ml Platform Jobs (NOW HIRING)

Jobtailor

Software Engineer, ML Platform

California, MO · On-site

$140 - $200/hr

Build core components of the ML and AI Platform technical roadmap, including MLOps solutions with automated pipelines and standardized processes to build, deploy, run, monitor, debug, and retrain ML ...

SumerSports LLC

MLOps / ML Platform Engineer

$170K - $200K/yr

Qualifications * 4+ years of experience in ML platform, DevOps, or infrastructure engineering. * Deep knowledge of Kubernetes, CI/CD, containers, and cloud infrastructure (AWS, GCP, or Azure)

Guidewire Software

Senior AI/ML Platform Engineer

San Mateo, CA · On-site

$119K - $163K/yr

As a Senior AI/ML Platform Engineer, you will architect and scale the ML platform for data scientists and ML engineers that powers Guidewire's next-generation products. This is a high-impact role for ...

Paramount

Senior ML Platform Engineer

Burbank, CA · On-site

$130K - $195K/yr

ML Platform Engineer Department : Data & Insight Group Location: New York City, Los Angeles, San Francisco We are seeking a Sr. ML Platform Engineer who is excited to deploy MLOps products that shape ...

Toyota

Senior ML Platform Engineer

Plano, TX · On-site

$100K - $137K/yr

Architect cloud-native platform capabilities that power production ML workloads and support enterprise-scale adoption * Drive platform standardization by standing up SageMaker Unified Studio ...

Jobtailor

AI/ML Platform Engineer

Spring, TX · On-site

$147.05 - $230.85/hr

AI/ML Platform Engineer We are a dynamic centralized platform team dedicated to harnessing cutting‑edge AI/ML technology, particularly in the realm of Generative AI and large language models, to ...

Paramount

Senior ML Platform Engineer

Burbank, CA

$130K - $195K/yr

Job Title: Sr. ML Platform Engineer Department : Data & Insight Group Location: New York City, Los Angeles, San Francisco We are seeking a Sr. ML Platform Engineer who is excited to deploy MLOps ...

Paramount

Senior ML Platform Engineer

Manhattan, NY · On-site

$130K - $195K/yr

Job Title: Sr. ML Platform Engineer Department : Data & Insight Group Location: New York City, Los Angeles, San Francisco We are seeking a Sr. ML Platform Engineer who is excited to deploy MLOps ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 Software Engineer III - AI/ML Platform Operations - Remote (Open) Location Arizona - Home Teleworkers ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 Software Engineer III - AI/ML Platform Operations - Remote (Open) Location Arizona - Home Teleworkers ...

Paramount Pictures

Senior ML Platform Engineer

Burbank, CA · On-site

$130.20 - $195.30/hr

You will build the foundations of our ML platform that will enable the Data Science team to deploy models at web scale data driving interactions with millions of customers across the globe. Specific ...

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ML Platform information

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$33

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$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

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 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.

Software Engineer, ML Platform

Jobtailor

California, MO • On-site

$140 - $200/hr

Other

Posted 5 days ago

Job description

Requirements
  • At least 5+ years of software engineering experience
  • Proficiency in Python, Ruby, or Java
  • Experience designing and developing machine learning lifecycle infrastructure and platform services
  • Experience with feature stores, model development, deployment, and observability tools and solutions
  • Experience with at least one major cloud platform; AWS preferred but not required
  • Curiosity and experimentation with emerging AI frameworks
  • Comfort with AI-assisted development tools
  • Ability to stay current with emerging software development approaches
  • Build core components of the ML and AI Platform technical roadmap, including MLOps solutions with automated pipelines and standardized processes to build, deploy, run, monitor, debug, and retrain ML and AI models
  • Develop, maintain, and enhance frameworks for machine learning model development and deployment
  • Collaborate with ML/AI builders and application owners to determine business requirements and SLAs for API-enabled services
  • Develop, maintain, and enhance infrastructure supporting machine learning services
  • Develop new deployment patterns for machine learning models with CI/CD pipelines and automated testing
  • Apply AI tools in the engineering workflow and bring an AI-native lens to engineering and product decisions
  • Adopt best practices for using AI technologies across technical development
Core Competencies

Demonstrates expertise in building and enhancing machine learning and AI platforms, focusing on MLOps solutions, automated pipelines, and infrastructure development. Proficient in Python, Ruby, or Java, with a strong understanding of cloud platforms and AI tools to drive innovative engineering practices.

Highest-signal resume keywords
  • MLOps Solutions
  • Machine Learning Lifecycle Infrastructure
  • CI/CD Pipelines
  • Python Programming
  • Cloud Platform Experience
ATS Optimization Keywords Hard Skills
  • Machine Learning Model Development
  • Automated Testing
  • API Development
  • Feature Stores
  • Model Deployment
  • Observability Tools
  • Infrastructure Development
  • AI Tools Application
  • Software Engineering
  • Emerging AI Frameworks
Soft Skills
  • Curiosity
  • Experimentation
Industry Keywords
  • MLOps
  • Automated Pipelines
  • Standardized Processes
  • AI-Native Engineering
  • Business Requirements
  • Service Level Agreements
Tools & Technologies
  • AWS
  • Ruby
  • Java
  • Python
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