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Machine Learning Infrastructure Engineer Jobs in San Jose, CA

Maven Robotics

ML Infrastructure Engineer

San Francisco, CA

$126K - $166K/yr

Role Description We are looking to recruit an exceptional Infrastructure Engineer to own and build the backend systems that power machine learning at Maven Robotics. In this role, you will design and ...

Maven Robotics

ML Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

Role Description We are looking to recruit an exceptional Infrastructure Engineer to own and build the backend systems that power machine learning at Maven Robotics. In this role, you will design and ...

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All JobsMachine Learning Infrastructure Engineer JobsMachine Learning Infrastructure Engineer Jobs in San Jose, CA

Machine Learning Infrastructure Engineer information

See San Jose, CA salary details

$54.5K

$148.9K

$213.3K

How much do machine learning infrastructure engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for machine learning infrastructure engineer in San Jose, CA is $148,920.00, according to ZipRecruiter salary data. Most workers in this role earn between $126,000.00 and $165,200.00 per year, depending on experience, location, and employer.

What is a machine learning infrastructure engineer?

A Machine Learning Infrastructure Engineer designs, builds, and maintains the systems that support the development and deployment of machine learning models. This includes managing data pipelines, optimizing model training and inference, and ensuring scalability and reliability in production environments. They work closely with data scientists, ML engineers, and DevOps teams to create efficient workflows and infrastructure. Key technologies often include cloud platforms, containerization, orchestration tools, and distributed computing frameworks.

What are the key skills and qualifications needed to thrive as a machine learning infrastructure engineer?

To thrive as a Machine Learning Infrastructure Engineer, you need a strong background in computer science, cloud computing, distributed systems, and experience with machine learning frameworks, often supported by a degree in a related field. Familiarity with tools such as Docker, Kubernetes, Terraform, as well as cloud platforms like AWS, GCP, or Azure, and certifications in cloud or DevOps technologies are highly valued. Strong problem-solving abilities, effective communication, and collaboration skills help engineers work seamlessly with data scientists and cross-functional teams. These skills are essential to design, implement, and maintain robust, scalable infrastructure that enables efficient machine learning development and deployment.

What are some common challenges faced by machine learning infrastructure engineers, and how can these be addressed on the job?

Machine Learning Infrastructure Engineers often face challenges such as ensuring infrastructure scalability, managing resource allocation, and maintaining system reliability while supporting rapid experimentation by data science teams. Balancing the needs for flexibility in research environments with production-grade stability requires a deep understanding of both engineering best practices and the unique requirements of machine learning workflows. Collaboration with data scientists, clear communication about infrastructure capabilities, and staying current with fast-evolving technologies are key strategies for success. Most companies encourage ongoing learning and provide opportunities to contribute to architecture decisions, which makes this a rewarding environment for problem-solvers and innovators.

What are popular job titles related to Machine Learning Infrastructure Engineer jobs in San Jose, CA?

For Machine Learning Infrastructure Engineer jobs in San Jose, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Infrastructure Engineer jobs in San Jose, CA look for?

The top searched job categories for Machine Learning Infrastructure Engineer jobs in San Jose, CA are:

What cities near San Jose, CA are hiring for Machine Learning Infrastructure Engineer jobs?

Cities near San Jose, CA with the most Machine Learning Infrastructure Engineer job openings:

Machine Learning Infrastructure Engineer jobs near you
Infographic showing various Machine Learning Infrastructure Engineer job openings in San Jose, CA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $148,920 per year, or $71.6 per hour.

Machine Learning Engineer

PROPRIUS

San Francisco, CA

Full-time

Re-posted 9 days ago

Job description

Machine Learning Engineer

Location: San Francisco, CA

Sponsorship: No

Relocation: No

Industry: Machine Learning

Join an artificial intelligence company in San Francisco that excels at visual recognition and is looking for a new ML engineer to join their team. Become part of a collaborative team that tackles research problems through a process of prototyping, implementation, measurement, and iteration. You will implement state-of-the-art deep learning techniques to help develop innovative AI products.

As a ML Engineer, you will:

  • Work with the research team to improve the visual search products
  • Train models with curated data to evaluated and ultimately improve performance
  • Deploy production-ready models to customers
  • Help maintain the machine learning infrastructure

For this role you will need:

  • MS. Degree
  • Experience with Python
  • Computer Vision or NLP experience
  • Experience debugging complex systems.
  • (Kuberentes or Docker experience would be a plus).

This is an amazing opportunity to join a team and work on large projects using powerful computer vision/deep learning technology.

PROPRIUS is an AI Industry recruiting firm. We’re lucky enough to recruit the best candidates into the most exciting companies all over the United States. We deliver performance.