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Machine Learning Platform Engineer Jobs (NOW HIRING)

Faire

Senior Staff Machine Learning Platform Engineer

$295K - $405K/yr

About this role As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of Faire's ML platform. You will set standards, influence org-wide architecture ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $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 ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $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 ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $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 Aug 21, 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?

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 does a machine learning platform engineer do?

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 skills and qualifications are needed to thrive as a machine learning platform engineer?

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.

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Machine Learning Platform Engineer jobs near you
Infographic showing various Machine Learning Platform Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $133,026 per year, or $64 per hour.

Machine Learning Platform Engineer - Backend Services (Utah)

Waystar

Atlanta, GA • On-site

Full-time

Re-posted 18 days ago

Job description

Job Summary:
Waystar is a leading company in healthcare payment solutions, seeking a Machine Learning Platform Engineer - Backend Services to enhance their platform for predictive models and data analysis. The role involves developing and maintaining machine learning frameworks, collaborating with data science teams, and ensuring the reliability of production systems.
Responsibilities:
• Develop and enhance the machine learning platform to manage the full model life cycle
• Build frameworks and tools to enable the data science team developing and enhancing predictive models, support scalable real-time predictions in production
• Design and implement data engineering solutions for model training
• Expand NLP capabilities with advanced analysis techniques to improve text understanding
• Design and implement high-performance, scalable services and applications
• Collaborate with team members to create integrated solutions and ensure timely delivery of quality software and documentation
• Understand and adhere to development standards for consistency across teams
• Perform in-depth technical and performance analyses to troubleshoot production issues
• Monitor and maintain production systems for reliability and efficiency
Qualifications:
Required:
• Bachelor’s degree in Computer Science or related area, Masters preferred
• 7+ years of professional experience writing Python or Java code, with at least 3 years building data platforms
• Expert proficiency with SQL
• NLP
• Seasoned practitioner of engineering best practices such as CI/CD and automated testing
• Comfort working in a Linux environment
• Passion for exploring, applying and following the evolution of cutting edge technologies related to AI, machine learning, NLP and large scale data processing
• Professional experience with MLOps, Docker, Kubernetes, relational databases (PostgreSQL preferred), Kafka, REST API design, and microservices application architectures
• Experience with public cloud solutions, such as AWS or GCP
• Proven track record of successful delivery of progressively complex technical projects
• Coaching and mentoring junior engineers in the team
• Team player DNA with a positive, self-starter attitude
• Attention to detail, highly organized, with an absolute focus on quality of work
Preferred:
• Familiarity with ClearML, Triton, PyTorch, and TensorFlow
• Familiarity with statistics and healthcare domain
• Proven expertise in successful large project/build management and execution
Company:
Waystar is a technology platform that provides healthcare revenue cycle management solutions. Founded in 2017, the company is headquartered in Louisville, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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