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Ml Platform Jobs (NOW HIRING)

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 ...

OR · On-site

$232K - $243K/yr

Liftoff is seeking a Director of Product Management, ML Platform to holistically own the product strategy and execution for our machine learning infrastructure. This is a senior, hands-on leadership ...

Key job responsibilities - Building ML platform services with Tier-1 availability and performance characteristics while enabling rapid model iteration and experimentation for scientists. - Evolving ...

Key job responsibilities - Building ML platform services with Tier-1 availability and performance characteristics while enabling rapid model iteration and experimentation for scientists. - Evolving ...

Key job responsibilities - Building ML platform services with Tier-1 availability and performance characteristics while enabling rapid model iteration and experimentation for scientists. - Evolving ...

Showing results 21-40

Ml Platform information

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$33

$63

$94

How much do ml platform jobs pay per hour?

As of Aug 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
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 77% Physical, 2% Hybrid, and 21% Remote job distribution, with an average salary of $133,026 per year, or $64 per hour.

Senior AI/ML Platform Engineer

Guidewire Software

San Mateo, CA • On-site

$119K - $163K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 23 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. ¹
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 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
High-priority opening - we're moving fast and looking to hire ASAP.
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).
  • Advanced experience 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 - $247,000. 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.