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Machine Learning Platform Engineer Jobs (NOW HIRING)

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$104.40K - $143.40K/yr

As a Senior Machine Learning Platform Engineer, you will architect and scale the ML platform that powers Guidewire's next-generation products. This is a high-impact role for a technical leader ...

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112.20K - $154K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... Proven experience with distributed systems , cloud platforms (AWS preferred), containerization and ...

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... Proven experience with distributed systems , cloud platforms (AWS preferred), containerization and ...

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112.20K - $154K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... Proven experience with distributed systems , cloud platforms (AWS preferred), containerization and ...

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Machine Learning Platform Engineer information

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How much do machine learning platform engineer jobs pay per hour?

As of May 30, 2026, the average hourly pay for machine learning 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 a Machine Learning Platform Engineer job?

A Machine Learning Platform Engineer designs, builds, and maintains the infrastructure that enables machine learning development and deployment at scale. They work on areas like data pipelines, model training workflows, monitoring, and cloud or on-premises platforms to ensure ML models run efficiently in production. Their role bridges software engineering and machine learning, focusing on automation, scalability, and reliability to support data scientists and ML engineers in delivering models faster and more effectively.

What are the key skills and qualifications needed to thrive in the Machine Learning Platform Engineer position, and why are they important?

A Machine Learning Platform Engineer should have strong programming skills (especially in Python or Java), knowledge of machine learning frameworks (like TensorFlow or PyTorch), and experience with cloud platforms and scalable infrastructure. Familiarity with containerization tools (such as Docker and Kubernetes), CI/CD systems, and relevant certifications in cloud or machine learning technologies is highly valued. Effective problem-solving, teamwork, and clear communication are crucial soft skills for collaborating across data science and engineering teams. These capabilities enable seamless creation and maintenance of robust, high-performance machine learning platforms for scalable model development and deployment.

What does a typical day look like for a Machine Learning Platform Engineer?

A typical day for a Machine Learning Platform Engineer involves designing, building, and maintaining the infrastructure that supports data science and machine learning workflows. You might spend your time developing new features for the platform, optimizing data pipelines, deploying models, and troubleshooting technical issues alongside data scientists and engineers. Collaboration is key—you’ll often work closely with cross-functional teams to understand requirements, ensure scalability, and improve the overall machine learning lifecycle. This role offers a challenging mix of software engineering and system design, so adaptability and a proactive mindset are important for success.
What cities are hiring for Machine Learning Platform Engineer jobs? Cities with the most Machine Learning Platform Engineer job openings:
What states have the most Machine Learning Platform Engineer jobs? States with the most job openings for Machine Learning Platform Engineer jobs include:
Infographic showing various Machine Learning Platform Engineer job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, 4% Part Time, 1% Temporary, and 7% Contract. Highlights an 97% Physical, 2% Hybrid, and 1% Remote job distribution, with an average salary of $133,026 per year, or $64 per hour.
Senior Machine Learning Platform Engineer

Senior Machine Learning Platform Engineer

Guidewire Software

Remote

$107K - $146.90K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago


Job description

Summary
Join Guidewire's Product Development & Operations (PDO) team, where we deliver operational excellence and transformative innovation for the world's leading P&C insurance software. Our team is at the forefront of AI, cloud, and data platform adoption, working collaboratively in a hybrid environment to ensure secure, scalable, and efficient solutions. We thrive on curiosity, continuous improvement, and a culture that values diverse perspectives and teamwork.
As a Senior Machine Learning Platform Engineer, you will architect and scale the ML platform that powers Guidewire's next-generation products. This is a high-impact role for a technical leader passionate about distributed systems, MLOps, and empowering data-driven innovation. You will help shape the future of insurance technology by enabling seamless ML workflows and accelerating the adoption of AI across Guidewire's solutions.
Job Description
What you'll do
  • Architect and guide the design of a scalable, secure ML platform supporting the full ML lifecycle, from data ingestion to model monitoring.
  • Design and implement infrastructure for model training, hyperparameter tuning, experiment tracking, and model registry.
  • Orchestrate ML workflows using tools such as Kubeflow, SageMaker, MLflow, or similar.
  • Collaborate with Data Scientists, MLOps engineers, Data Engineers, and Product Engineering to define best practices for reproducibility, governance, and CI/CD for ML.
  • Partner with Data Engineers to build robust data pipelines for model-ready datasets.
  • Optimize ML workload performance across compute and storage layers using cloud-native and open-source solutions.
  • Lead technical discussions, mentor junior engineers, and help set the technical vision for the ML platform roadmap.
  • Ensure compliance with security, privacy, and regulatory requirements throughout the ML lifecycle.
  • At Guidewire, we foster a culture of curiosity, innovation, and responsible use of AI-empowering our teams to continuously leverage emerging technologies and data-driven insights to enhance productivity and outcomes.

What you'll bring
Required
  • Demonstrated ability to embrace AI and apply it to your current role as well as data-driven insights to drive innovation, productivity, and continuous improvement.
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 10+ years of software engineering experience, including 5+ years working on ML platforms or infrastructure.
  • Expertise in building large-scale distributed systems and microservices.
  • Strong programming skills in Python, Go, or Java.
  • Experience with containerization and orchestration (e.g., Docker, Kubernetes).
  • Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Databricks.
  • Cloud platform experience (AWS, GCP, or Azure).
  • Experience with statistical learning algorithms (GLM, XGBoost, Random Forest) and deep learning (neural networks, transformers).
  • Strong communication, leadership, and problem-solving skills.

Preferred
  • Experience with real-time model inference and streaming ML pipelines.
  • Deep knowledge of model governance, reproducibility, and monitoring.
  • Understanding of model performance metrics and drift detection.
  • Exposure to feature stores (Feast, Tecton) and workflow tools (Airflow, Argo).
  • Familiarity with regulatory considerations (model auditability, interpretability, data privacy laws such as CCPA/GDPR).
  • Experience with real-time data pipelines (Kafka, Flink, Spark Structured Streaming).
  • Experience using TeamCity and Terraform for infrastructure setup and CI/CD.
  • Insurance industry or related experience (banking, finance).

Your Impact
We believe in clarity and setting you up for success. In your first six months, you'll lead the design and implementation of core ML platform components, collaborate with cross-functional teams to deliver scalable solutions, and establish best practices for ML operations. Your work will directly support Guidewire's mission to deliver secure, efficient, and innovative insurance technology, driving measurable value for our customers and accelerating the adoption of AI and cloud capabilities. Over time, your leadership will influence the technical direction of our ML platform and empower teams across the company.
What's in it for you
The people we employ give their all, and in return, we offer flexibility wherever we can, such as:
  • Flexible work environment
  • Health and wellness benefits
  • Paid time off programs, including volunteer time off
  • Market-competitive pay and incentive programs
  • Continual development and internal career growth opportunities
  • A new in-person orientation process for all roles

At Guidewire, you'll help transform the insurance industry, working alongside a collaborative, innovative team committed to customer success and continuous improvement. Your contributions will support our wider mission to deliver measurable value, efficiency, and success for customers through secure, scalable, and AI-powered solutions.
The US base salary range for this full-time position is $148,000 - $222,000 . 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 Accommodations@guidewire.com. 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 Accommodations@guidewire.com 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 www.guidewire.com 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.