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Machine Learning Platform Engineer Jobs (NOW HIRING)

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

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Machine Learning Platform Engineer information

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$33

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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.

More about Machine Learning Platform Engineer jobs

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 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.

Senior Software Engineer, Machine Learning Platform

Menlo Ventures

San Francisco, CA • On-site

$187 - $259/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Job description

About the role

Chime’s Machine Learning Platform (MLP) team builds and operates the infrastructure, tooling, and developer experience that powers machine learning across the company. We enable data scientists and ML engineers to develop, train, deploy, and monitor models reliably and efficiently.

As a Machine Learning Platform Engineer, you will design and build scalable systems that support model training, feature computation, real‑time inference, and experimentation. You’ll work at the intersection of distributed systems, cloud infrastructure, and applied machine learning.

This role focuses on building robust foundations that allow ML teams to move quickly while maintaining reliability, governance, and cost efficiency.

The base salary offered for this role and level of experience will begin at $187,000.00 and goes up to $259,000.00. Full‑time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to
  • Design, build, and operate scalable ML infrastructure on AWS
  • Develop distributed training and batch processing systems using Ray
  • Build and maintain infrastructure-as-code using Terraform
  • Support and evolve the feature store and feature pipelines
  • Develop data ingestion and streaming systems (e.g., Kinesis, Kafka, Flink, Spark, or similar technologies)
  • Improve CI/CD workflows for ML models and platform components
  • Enhance observability, reliability, and cost visibility across ML workloads
  • Partner closely with Data Science and ML Engineering teams to improve developer experience
  • Contribute to platform architecture decisions and technical roadmaps
  • Participate in on‑call rotations to support production systems
To thrive in this role, you have
  • 5+ years of experience in ML infrastructure, platform engineering, or production ML systems
  • Knowledge of the machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment
  • Experience with distributed systems, cloud computing, or large‑scale data processing
  • Strong foundation in computer science and software engineering principles
  • Deeply interested in the impact and evolution of advanced AI technologies
  • Hands‑on experience with CI/CD pipelines, DevOps practices, and infrastructure as code
  • Experience with containerization technologies such as Docker and Kubernetes, and orchestration systems
  • Knowledge of cloud platforms such as AWS and distributed computing frameworks such as Spark and Ray
  • Experience with GPU programming (CUDA) and GPU costs/optimization
  • Strong programming skills in Python, Go, Scala, Java or similar languages
  • Familiarity with infrastructure‑as‑code (e.g., Terraform, CloudFormation)
  • Solid understanding of software engineering fundamentals (testing, version control, code review, observability)
Nice-to-have
  • Experience with distributed compute frameworks such as Ray
  • Experience building or operating a feature store
  • Experience with real‑time ML systems or model serving
  • Familiarity with streaming technologies (Kafka, Kinesis, Flink, Spark Streaming, etc.)
  • Experience supporting ML lifecycle workflows (training, evaluation, deployment, monitoring)
  • Knowledge of ML experimentation platforms and model governance practices
What we offer for our full‑time, regular employees
  • Our in‑office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company‑wide events depending on location. Whether you’re coming in regularly or are part of our fully remote program, you’ll stay engaged with your work and teammates.
  • In‑office perks including backup child, elder, and/or pet care, plus a subsidized commuter benefit to support your regular commute
  • Competitive salary based on experience
  • 401k match plus great medical, dental, vision, life, and disability benefits
  • Generous vacation policy and company‑wide Chime Days, bonus company‑wide paid days off
  • 1% of your time off to support local community organizations of your choice
  • Annual wellness stipend to use towards eligible wellness related expenses
  • Up to 24 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non‑birthing parents
  • Access to Maven, a family planning tool, with $15k lifetime reimbursement for egg freezing, fertility treatments, adoption, and more.
  • In‑person and virtual events to connect with your fellow Chimers—think cooking classes, guided meditations, music festivals, mixology classes, paint nights, etc., and delicious snack boxes, too!
  • A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress

Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: benefits@chime.com.

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