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Machine Learning Platform Engineer Jobs in California

Roku

Senior Machine Learning Engineer

San Jose, CA

$148.75K - $361K/yr

At the core of this is our Machine Learning, Experimentation and Inference Platform that powers the ... We're looking for strong engineers well versed with modern large scale machine learning platforms ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us ... NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us ... NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize ...

Vurke Inc

Data Platform Engineer

Union City, CA · Remote

$130.40K - $156.60K/yr

... machine learning use cases. In this role, you will focus on the technical platform side of data, including scalability, orchestration, storage patterns, reliability, and engineering standards. You ...

Adobe, Inc.

Machine Learning Engineer

San Jose, CA · On-site

Machine Learning Engineer The Opportunity Join Adobe and be at the forefront of driving digital ... platforms and tools that unleash creativity, productivity and personalized customer experiences.

Apple

Machine Learning Engineer

Cupertino, CA · On-site

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive ... similar platforms.Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.

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Machine Learning Platform Engineer information

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.
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Machine Learning Platform Engineer jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Roku

San Jose, CA

$148.75K - $361K/yr

Other

Medical, Life, PTO

Posted 15 days ago

Job description

About the team  

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers and Roku. The systems and solutions span across different disciplines and technologies to perform realtime multi-objective optimization with distributed systems at large scale and low latencies. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation and Inference Platform that powers the entire landscape which we continuously evolve over time.

About the role  

In this role you will apply various methodologies to solve a large variety of challenging problems in Advertising related to conversion modeling aligned with attribution methodologies/models, calibration, dynamic creative generation and optimization, forecasting and timeseries modeling, yield and margin optimization and Experimentation for A/B and multivariate testing. You will also work on building out a SOTA machine learning platform.  

We're looking for strong engineers well versed with modern large scale machine learning platforms with a solid grasp of core statistical techniques and deep experience in SOTA Deep Learning discriminative and generative models.

For California Only - The estimated annual salary for this position is between $148,750 - $361,000 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.

What you'll be doing 
  • Building SOTA Deep learning discriminative models and build generative models to generate image and video ads geared towards optimizing performance
  • Building and evolving a SOTA Machine Learning Platform from feature generation to realtime inferencing that can optimize and deploy complex models at large scale and low latencies
  • Be forward thinking about advancements in ML related areas
We're excited if you have  
  • BS or higher in CS, ECE or a related field  
  • 5+ years of experience in building out Machine Learning platforms or applying Deep Learning  methodologies
  • Ability to communicate and collaborate cross functionally   

Preferred Qualifications:  

  • MS or higher CS, ECE or a related field
  • Experience in the Advertising domain
  • Contributions to open-source ML projects 
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