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Ai Platform Engineer Jobs in California (NOW HIRING)

IMCS Group

AI Platform Engineer

Woodland, CA · On-site

AI Platform Engineer Location: Wood Land Hills, CA(Onsite) Duration: 6+ months contract Need 10+ Years Profile We are seeking a highly skilled AI Platform Engineer to design, build, and maintain ...

Tessera Labs

AI Platform Engineer

San Francisco, CA

$200K - $250K/yr

AI Platform Engineer About Tessera Labs Tessera Labs is redefining how enterprises adopt and operationalize Artificial Intelligence. Backed by Foundation Capital and led by a world-class founding ...

Axos Bank

AI Platform Engineer

San Diego, CA · On-site

$130K - $150K/yr

About This Job Axos Bank is hiring an AI Platform Engineer to engineer, operate, and help govern the platforms and infrastructure that power the bank's AI and automation capabilities. This is a hands ...

Axos Bank

AI Platform Engineer

San Diego, CA · On-site

$130K - $150K/yr

About This Job Axos Bank is hiring an AI Platform Engineer to engineer, operate, and help govern the platforms and infrastructure that power the bank's AI and automation capabilities. This is a hands ...

KPI Partners

Azure AI Platform Engineer

Fremont, CA · On-site

$75 - $85/hr

Title: Azure AI Platform Engineer Location: Fremont, CA (Remote with Travel) Job Type: Contract - 12 Months Pay Rate: $75/hr - $85/hr Key Skills: Azure AI Foundry, Microsoft Foundry, Azure ...

Notable

AI Platform Engineer

San Mateo, CA · On-site

$170K - $205K/yr

Notable builds AI-driven automation for healthcare. As a Senior AI Platform Engineer, you will design, build, and maintain LLM integrations that power AI features across Notable's solutions. You'll ...

Applied Compute

AI Platform Engineer

San Francisco, CA · On-site

$190K - $310K/yr

The role As an AI platform engineer, you'll build the products, interfaces, and tools that define how people interact with Applied Compute's agents. You'll own the full stack of our application ...

Airbyte

AI Platform Engineer

San Francisco, CA · On-site

$196K - $235K/yr

... AI frameworks. * Strong software engineering fundamentals including APIs, concurrency, testing, and system design. * Experience building developer platforms, orchestration systems, or workflow ...

BrainCo

AI Platform Engineer, DevX

San Francisco, CA · On-site

... engineer at BrainCo can ship. As we grow from a handful of teams to dozens - building AI systems for governments and regulated industries - the platform that lets us move quickly without breaking ...

Adobe

Senior AI Platform Engineer

San Francisco, CA

$123K - $169K/yr

The AI for Engineering team builds a scalable, production-grade AI platform that powers creativity across design, imaging, motion, and personalization. We are seeking a Staff Engineer - AI for ...

Adobe, Inc.

Senior AI Platform Engineer

San Jose, CA · On-site

$122K - $168K/yr

The AI for Engineering team builds a scalable, production-grade AI platform that powers creativity across design, imaging, motion, and personalization. We are seeking a Staff Engineer - AI for ...

Adobe

Senior AI Platform Engineer

San Jose, CA · On-site

$122K - $168K/yr

They are seeking a Staff Engineer - AI for Engineering to design and build the next-generation AI systems that enhance creativity and engineering productivity across their platforms. Responsibilities ...

Afresh Company

Senior AI Platform Engineer

San Francisco, CA · On-site

$144K - $190K/yr

As a Senior AI Platform Engineer , you build the AI and data platform that powers Afresh's products: the knowledge and retrieval layer that makes grocery data reliably usable by LLMs, the agent ...

Adobe

Senior AI Platform Engineer

San Jose, CA

$122K - $168K/yr

The AI for Engineering team builds a scalable, production-grade AI platform that powers creativity across design, imaging, motion, and personalization. We are seeking a Staff Engineer - AI for ...

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All JobsAi Platform Engineer JobsAi Platform Engineer Jobs in California

Ai Platform Engineer information

See California salary details

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$63

$93

How much do ai platform engineer jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for ai platform engineer in California is $63.12, according to ZipRecruiter salary data. Most workers in this role earn between $49.81 and $72.84 per hour, depending on experience, location, and employer.

What is an AI Platform Engineer?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

What are the key skills and qualifications needed to thrive as an AI Platform Engineer, and why are they important?

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

How to become an AI platform engineer?

To become an AI platform engineer, you should have a strong background in computer science, software engineering, or related fields, with expertise in machine learning frameworks, cloud computing, and programming languages like Python or Java. Gaining experience with AI tools, data management, and infrastructure deployment is essential, often supported by certifications in cloud platforms such as AWS or Azure. Building a portfolio of projects and staying updated on AI and DevOps practices can also enhance your qualifications.

What does an AI platform engineer do?

An AI platform engineer designs, develops, and maintains the infrastructure and tools needed to deploy and manage artificial intelligence models at scale. They work with cloud services, programming languages, and machine learning frameworks to ensure efficient model training, deployment, and monitoring in production environments.

What is the salary of AI platform engineer?

The salary of an AI platform engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and machine learning may earn higher compensation.

What are popular job titles related to Ai Platform Engineer jobs in California?

For Ai Platform Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Ai Platform Engineer jobs in California look for?

The top searched job categories for Ai Platform Engineer jobs in California are:

What cities in California are hiring for Ai Platform Engineer jobs?

Cities in California with the most Ai Platform Engineer job openings:

Ai Platform Engineer jobs near you
Infographic showing various Ai Platform Engineer job openings in California as of August 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 64% In-person, and 36% Remote job distribution, with an average salary of $131,284 per year, or $63.1 per hour.

AI Platform Engineer

IMCS Group

Woodland, CA • On-site

Other

This job post has expired 3 days ago. Applications are no longer accepted.

Job description

Hi,

Hope you are doing well.

Please go through the below Job Description and I would humbly request you to apply with your latest resume. Our goal is not to just submit your profile but to secure an interview for you. If this email/Job Description has reached out to you in error, please accept my sincere apologies and disregard the email. Notify us via email, and we'd immediately remove you from consideration.


Job Title: AI Platform Engineer

Location: Wood Land Hills, CA(Onsite)

Duration: 6+ months contract


Need 10+ Years Profile


Job Description:

We are seeking a highly skilled AI Platform Engineer to design, build, and maintain scalable AI and machine learning platforms that enable data scientists and AI engineers to develop, deploy, monitor, and optimize AI models efficiently. The ideal candidate will have expertise in cloud computing, MLOps, infrastructure automation, containerization, and AI/ML technologies.


The AI Platform Engineer will work closely with Data Scientists, ML Engineers, Software Engineers, and DevOps teams to deliver secure, reliable, and scalable AI solutions across the enterprise.


Key Responsibilities:

  • Design, develop, and manage enterprise-grade AI/ML platforms and infrastructure.
  • Build and maintain MLOps pipelines for model training, deployment, monitoring, and governance.
  • Develop scalable environments for machine learning workloads using cloud-native technologies.
  • Automate AI model deployment and lifecycle management using CI/CD practices.
  • Implement model monitoring, observability, logging, and performance tracking solutions.
  • Optimize infrastructure for large-scale AI workloads, including GPU and distributed computing environments.
  • Collaborate with data science teams to operationalize machine learning models.
  • Ensure platform security, compliance, and governance standards are met.
  • Evaluate and integrate emerging AI technologies, frameworks, and tools.
  • Troubleshoot platform issues and improve reliability, scalability, and efficiency.


Required Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
  • 5+ years of experience in Platform Engineering, DevOps, Cloud Engineering, or MLOps.
  • Strong programming experience in Python, Java, or Go.
  • Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Experience with containerization technologies such as Docker and Kubernetes.
  • Expertise in cloud platforms such as Azure, AWS, or Google Cloud Platform.
  • Strong knowledge of CI/CD tools such as GitHub Actions, GitLab CI, Jenkins, or Azure DevOps.
  • Experience with Infrastructure as Code (Terraform, CloudFormation, ARM/Bicep).
  • Knowledge of model serving platforms such as MLflow, Kubeflow, Ray, SageMaker, or Azure Machine Learning.
  • Strong understanding of distributed systems, APIs, and microservices architecture.


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