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Ml Platform Engineer Jobs (NOW HIRING)

Guidewire Software Inc.

ML Platform Engineer

San Mateo, CA · On-site

$124K - $210K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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 ...

Guidewire Software

ML Platform Engineer

San Mateo, CA · On-site

$124K - $210K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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 ...

Guidewire Software

ML Platform Engineer

San Mateo, CA · On-site

$124K - $210K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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 ...

Stitch Fix

ML Platform Engineer

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.

Stitch Fix

ML Platform Engineer

$136K - $167K/yr

  • Medical

  • Dental

  • Vision

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.

Hadrian Automation

ML Platform Engineer

Los Angeles, CA · On-site

$170K - $300K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... platform engineers. What We're Looking For * Track record building and operating production ML infrastructure across multiple models or inference workloads. * Strong production-level Python and SQL ...

Hadrian Automation, Inc

ML Platform Engineer

Los Angeles, CA · On-site

$170K - $300K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... platform engineers. What We're Looking For * Track record building and operating production ML infrastructure across multiple models or inference workloads. * Strong production-level Python and SQL ...

Avride

Software Engineer - ML Platform

Austin, TX · On-site

We sit between Cloud Platform and ML engineers, turning low-level compute, storage, and networking primitives into an ML platform that teams actually use - scalable orchestration, distributed compute ...

Allen Control Systems

CV/ML Platform Engineer

Austin, TX · On-site

  • Medical

  • Dental

  • Vision

  • PTO

Position Overview We are seeking an experienced CV/ML Platform Engineer with specialization in Computer Vision and Machine Learning (CV/ML) to design, build, and own the data, model, and compute ...

Paramount

Senior ML Platform Engineer

Burbank, CA · On-site

$130K - $195K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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

$130K - $195K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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

Burbank, CA · On-site

$130K - $195K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Allen Control Systems

CV/ML Platform Engineer

Austin, TX · On-site

  • Medical

  • Dental

  • Vision

  • PTO

Position Overview We are seeking an experienced CV/ML Platform Engineer with specialization in Computer Vision and Machine Learning (CV/ML) to design, build, and own the data, model, and compute ...

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All JobsMl Platform Engineer Jobs

Ml Platform Engineer information

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$33

$63

$94

How much do ml platform engineer jobs pay per hour?

As of Aug 16, 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 is an ML Platform Engineer?

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 skills and qualifications are needed to thrive as an ML Platform Engineer?

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.

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 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.

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Ml Platform Engineer jobs near you
Infographic showing various Ml Platform Engineer job openings in the United States as of August 2026, with employment types broken down into 52% Full Time, 44% Part Time, and 4% 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

Guidewire Software Inc.

San Mateo, CA • On-site

$124K - $210K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 17 days ago

Job description

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 closely with Data Scientists, Data Engineers, MLOps engineers, and Product Engineering teams to build reliable, secure, and scalable ML platform capabilities.
Job Description
What you'll do
Key responsibilities include:
  • Design, develop, and maintain components of a scalable and secure ML platform supporting the machine learning lifecycle, from data ingestion and model training to deployment and monitoring.
  • Build infrastructure for model training, experiment tracking, hyperparameter tuning, and model registry using tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or similar technologies.
  • Develop and maintain automated ML workflows and CI/CD pipelines for machine learning applications.
  • Collaborate with Data Scientists and Data Engineers to build reliable, model-ready datasets and improve the ML development experience.
  • Help optimize ML workloads across cloud infrastructure, compute, and storage to improve scalability and efficiency.
  • Contribute to platform reliability by implementing monitoring, logging, testing, and operational best practices.
  • Participate in design discussions, code reviews, and technical planning while contributing to engineering best practices.
  • Ensure platform components meet security, privacy, and compliance requirements.

At Guidewire, we foster a culture of curiosity, innovation, and responsible AI. We encourage engineers to leverage emerging AI capabilities and data-driven insights to improve engineering productivity and deliver secure, scalable solutions for the insurance industry.
What You'll Bring
Required Qualifications
  • Demonstrated ability to embrace AI and apply it in day-to-day engineering work to improve productivity and software quality.
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
  • 3+ years of software engineering experience, including experience building or supporting ML platforms, data platforms, or cloud-native applications.
  • Strong programming skills in Python, Go, or Java.
  • Experience with Docker and Kubernetes or similar container orchestration technologies.
  • Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Databricks.
  • Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Basic understanding of machine learning workflows and common algorithms.
  • Strong communication, collaboration, and problem-solving skills.
Preferred Qualifications
  • Experience deploying and monitoring machine learning models in production.
  • Familiarity with feature stores, workflow orchestration tools (Airflow, Argo), or model monitoring solutions.
  • Exposure to streaming technologies such as Kafka or Spark.
  • Experience with Infrastructure as Code and CI/CD tools such as Terraform and TeamCity.
  • Familiarity with ML governance, reproducibility, and model lifecycle management.
  • Experience in the insurance, financial services, or another regulated industry.

Your Impact
During your first six months, you will:
  • Deliver core ML platform capabilities that improve the productivity of machine learning teams.
  • Collaborate with cross-functional teams to build scalable, reliable, and secure ML infrastructure.
  • Contribute to automation, operational excellence, and engineering best practices across the ML platform.
  • Help improve the developer experience for building, deploying, and managing machine learning models.
  • Support Guidewire's AI initiatives by delivering robust platform capabilities that enable teams to build and operate ML solutions efficiently.
The US base salary range for this full-time position is $124,000 - $210,000. Your base pay will depend on your experience, skills, education, training, and location among other factors. All full-time positions or part-time roles working 30 hours or more a week at Guidewire are eligible for benefits that support their health and well-being including health, dental, and vision insurance, paid time off, and a company sponsored retirement plan. In addition, some roles may be eligible for the annual company bonus plan, commissions, and/or long term incentive awards which are contingent on a variety of factors including, but not limited to, company and employee performance.
Disability Accommodations and Guidewire's Appeals Process. Guidewire provides accommodations to the hiring process to create a fair opportunity for candidates with disabilities to contend for open positions. Accommodation requests should be directed to If things do not go as hoped, we invite you to use our appeals process. Guidewire promises to independently review any denied accommodation and any decision not to offer you the position. The appeals process is the same in either case. Within five business days of receiving a notice of denial of an accommodation, or receiving a notice of your non-selection for a vacancy, e-mail to make an appeal. Guidewire will assign a new decision-maker to review the request and/or hiring decision, who will then notify you in writing of a decision within 10 business days.
About Guidewire
Guidewire is the platform P&C insurers trust to engage, innovate, and grow efficiently. We combine digital, core, analytics, and AI to deliver our platform as a cloud service. More than 540+ insurers in 40 countries, from new ventures to the largest and most complex in the world, run on Guidewire.
As a partner to our customers, we continually evolve to enable their success. We are proud of our unparalleled implementation track record with 1600+ successful projects, supported by the largest R&D team and partner ecosystem in the industry. Our Marketplace provides hundreds of applications that accelerate integration, localization, and innovation.
For more information, please visit and follow us on Twitter: @Guidewire_PandC.
Guidewire Software, Inc. is proud to be an equal opportunity and affirmative action employer. We are committed to an inclusive workplace, and believe that a diversity of perspectives, abilities, and cultures is a key to our success. Qualified applicants will receive consideration without regard to race, color, ancestry, religion, sex, national origin, citizenship, marital status, age, sexual orientation, gender identity, gender expression, veteran status, or disability. All offers are contingent upon passing a criminal history and other background checks where it's applicable to the position.

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