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Mlops Machine Learning Engineer Jobs in Milpitas, CA

CYNET SYSTEMS

Machine Learning Engineer

San Jose, CA · On-site

$55 - $60/hr

Solid understanding of MLOps principles and experience with related tools (e.g., Vertex AI, CI/CD ... engineering and MLOps to ensure the quality, maintainability, and scalability of machine learning ...

Spark Tek Inc

Machine Learning Engineer

San Jose, CA · On-site

Spark Tek Inc is seeking a highly skilled Machine Learning Engineer to design and build a low ... MLOps practices, including: Monitoring and observability, Drift detection, Retraining pipelines ...

Clera

Senior Machine Learning Engineer

Palo Alto, CA · Remote

$145K - $156K/yr

About the Role This is a Senior Machine Learning Engineer role embedded within a growing AI and ... Develop and maintain MLOps pipelines including CI/CD, model registry, feature stores, automated ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

About the role: We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex ...

RADAR

Machine Learning Engineer

Sunnyvale, CA · Hybrid

$195K - $264K/yr

ABOUT THE JOB We are looking for a Machine Learning Engineer to help build and develop our ML ... Experience with MLOps tools (MLflow, Weights & Biases, etc.) At RADAR, your base pay is one part of ...

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

MM International

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

Expedia

Machine Learning Engineer III

San Jose, CA · On-site

$252K/yr

We are seeking a Machine Learning Engineer II to join our Advertising Technology team, where we ... This role sits at the intersection of machine learning, distributed systems, and MLOps, directly ...

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All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Milpitas, CA

Mlops Machine Learning Engineer information

See Milpitas, CA salary details

$36.7K

$150.1K

$225.5K

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

As of Sep 2, 2026, the average yearly pay for mlops machine learning engineer in Milpitas, CA is $150,064.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,300.00 and $180,600.00 per year, depending on experience, location, and employer.

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Milpitas, CA?

For Mlops Machine Learning Engineer jobs in Milpitas, CA, the most frequently searched job titles are:

What job categories do people searching Mlops Machine Learning Engineer jobs in Milpitas, CA look for?

The top searched job categories for Mlops Machine Learning Engineer jobs in Milpitas, CA are:

What cities near Milpitas, CA are hiring for Mlops Machine Learning Engineer jobs?

Cities near Milpitas, CA with the most Mlops Machine Learning Engineer job openings:

Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in Milpitas, CA as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 26% Part Time, 3% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $150,064 per year, or $72.1 per hour.

Machine Learning Engineer

CYNET SYSTEMS

San Jose, CA • On-site

$55 - $60/hr

Contractor

Medical, Dental, Vision, Life, Retirement

Posted 7 days ago

Job description

Job Overview:

Pay Range: $55.00hr - $60.00hr

Requirement/Must Have:

  • 3+ years of professional experience building and deploying machine learning models in a production environment.
  • Advanced proficiency in Python and its core data science/ML libraries (e.g., PyTorch, scikit-learn, Pandas).
  • Advanced proficiency in SQL for complex data manipulation, aggregation, and analysis.
  • Demonstrable, hands-on experience in prompt engineering and/or fine-tuning Large Language Models (e.g., Gemini).
  • Hands-on experience with a major cloud provider, with a strong preference for Google Cloud Platform (GCP).
  • Solid understanding of MLOps principles and experience with related tools (e.g., Vertex AI, CI/CD).

Responsibilities:

  • Design, develop, and fine-tune Generative AI solutions using models like Google’s Gemini for tasks such as information extraction, document summarization, and report generation.
  • Architect and implement advanced Retrieval-Augmented Generation (RAG) systems to enhance model accuracy and provide verifiable, context-aware responses.
  • Research and apply emerging GenAI techniques, such as agentic frameworks, to build more autonomous and capable systems.
  • Design and deploy a wide range of ML models (classification, regression, forecasting, etc.) on Google Cloud Platform.
  • Build and maintain robust, automated MLOps pipelines for data preprocessing, feature engineering, model training, validation, and deployment using tools like Vertex AI and BigQuery.
  • Conduct deep data analysis to uncover insights, validate hypotheses, and guide feature engineering for improved model performance.
  • Partner closely with data scientists, software engineers, and other business stakeholders to frame problem statements, define technical requirements and deliver integrated AI/ML solutions.
  • Champion best practices in software engineering and MLOps to ensure the quality, maintainability, and scalability of machine learning systems.
  • Continuously evaluate and stay current with the latest advancements in the ML and GenAI landscape.

Nice to Have:

  • Master’s or PhD in a relevant field.
  • Specific experience with GCP services like Vertex AI, BigQuery, Google Cloud Storage, and GKE.
  • Experience building RAG systems from the ground up.
  • Proven ability to lead technical projects and mentor other engineers.

Skills:

  • Python.
  • PyTorch.
  • scikit-learn.
  • Pandas.
  • SQL.
  • Generative AI.
  • Gemini.
  • Google Cloud Platform (GCP).
  • Vertex AI.
  • BigQuery.
  • MLOps.
  • RAG systems.

Qualification And Education:

  • Bachelor’s degree in Computer Science, Data Science, Statistics, or a related quantitative field.

Benefits:

Our Benefits Include:

  • Medical, Dental, and Vision Insurance
  • 401(k) Retirement Plan
  • Health Savings Account (HSA)
  • Disability Insurance (Short-Term and Long-Term)
  • Life and AD&D Insurance
  • Paid Sick Leave (where required by applicable state or local law)
  • Supplemental Insurance Plans
  • Identity Theft Protection
  • Pet Insurance
  • Employee Wellness Programs
  • Employee Assistance Program (EAP)
  • Career Growth and Professional Development Opportunities

Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws.


About Cynet Systems


Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia.

As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.

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About Cynet Systems

Sourced by ZipRecruiter

Cynet Systems Inc is a staffing and recruiting corporation nestled in Ashburn, VA, USA. Established in 2010, the company operates within the Information Technology and Services sector, specializing in providing effective workforce solutions to different business needs, including IT consulting, direct hire, and contract staffing services. Through the years, Cynet Systems has built an impressive portfolio, going beyond borders and expanding its operations internationally in Canada and India. Rooted in its core values of teamwork, leadership, and commitment, Cynet Systems helps businesses unlock their full potential by providing versatile and competent professionals that perfectly align with their needs. Fueled by their unwavering mission to deliver top-tier talent to businesses worldwide, Cynet Systems garnered various recognitions including SIA's fastest-growing staffing firms and Best Place to Work in Virginia for 2019.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Sterling, VA, US

Year founded

2010

Social media

Twitter

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