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Senior Machine Learning Engineer Jobs in Cupertino, CA

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 Data Science team at a healthcare-focused data and analytics company. You'll take end-to-end ownership ...

Clera

Senior Machine Learning Engineer

Palo Alto, CA · On-site

$96 - $103/hr

About the Role We are an IT services consultancy placing a Senior Machine Learning Engineer with one of our end clients - a growing healthcare technology organization focused on AI and Data Science.

MrBeast

Senior Machine Learning Engineer

San Mateo, CA · Hybrid

$119K - $163K/yr

Senior Machine Learning Engineer Primary: Bay Area (San Francisco / Peninsula) | Secondary: NYC The Opportunity We're doing an AI-first engineering rebuild for a company that already has an audience ...

Intuit

Senior Machine Learning Engineer

Mountain View, CA · On-site

$171K - $231K/yr

Senior Machine Learning Engineer Join a vibrant team of machine learning engineers helping conceive, code, and deploy AI science models at scale using the latest industry tools. As a Senior engineer ...

Intuit

Senior Machine Learning Engineer

Mountain View, CA · On-site

$171K - $231K/yr

Overview Senior Machine Learning Engineer Join a vibrant team of machine learning engineers helping conceive, code, and deploy AI science models at scale using the latest industry tools. As a Senior ...

Adobe

Senior Machine Learning Engineer

San Jose, CA · On-site

$172K - $306K/yr

What You'll Do As a Senior Machine Learning Engineer on the Content Intelligence team, you will lead the development of ML models and systems, to assist with Content Understanding. You will work ...

Unitytech

Senior Machine Learning Engineer

Mountain View, CA · On-site +1

$123K - $169K/yr

We're looking for a Senior Machine Learning Engineer to lead the development of these foundational AI systems within the Unity engine, empowering creators to build smarter, more responsive in-game ...

MrBeast

Senior Machine Learning Engineer

San Mateo, CA · On-site

$119K - $163K/yr

Senior Machine Learning Engineer Primary: Bay Area (San Francisco / Peninsula) | Secondary: NYC The Opportunity We're doing an AI-first engineering rebuild for a company that already has an audience ...

GEICO

Senior Machine Learning Engineer

Palo Alto, CA · On-site

$123K - $168K/yr

They are seeking a Senior Machine Learning Engineer to contribute to the generative AI space, collaborating with a team to design and deploy high-performance AI solutions that drive business value.

SAP

Senior Machine Learning Engineer

Palo Alto, CA · On-site

$140K - $185K/yr

As a Senior Machine Learning Engineer on this team you will be responsible for helping to design and implement a variety of projects around the GenAI space The Role: • Work closely with our lead ...

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Senior Machine Learning Engineer information

See Cupertino, CA salary details

$73.4K

$156.1K

$226.4K

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

As of Aug 30, 2026, the average yearly pay for senior machine learning engineer in Cupertino, CA is $156,139.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,900.00 and $177,000.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Cupertino, CA?

The most popular types of Machine Learning Engineer jobs in Cupertino, CA are:

What are popular job titles related to Senior Machine Learning Engineer jobs in Cupertino, CA?

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

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

The top searched job categories for Senior Machine Learning Engineer jobs in Cupertino, CA are:

What cities near Cupertino, CA are hiring for Senior Machine Learning Engineer jobs?

Cities near Cupertino, CA with the most Senior Machine Learning Engineer job openings:

Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Cupertino, CA as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 28% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $156,139 per year, or $75.1 per hour.

Senior Machine Learning Engineer

Clera

Palo Alto, CA • Remote

$145K - $156K/yr

Full-time

Posted 16 days ago

Job description

About the Role

This is a Senior Machine Learning Engineer role embedded within a growing AI and Data Science team at a healthcare-focused data and analytics company. You'll take end-to-end ownership of enterprise-scale ML solutions — from raw data through to production — playing a critical part in delivering compliant, high-impact AI capabilities in a regulated healthcare environment.

What You'll Do

  • Design, develop, deploy, and maintain enterprise-scale machine learning solutions from the ground up.

  • Build end-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and retraining.

  • Develop and maintain MLOps pipelines including CI/CD, model registry, feature stores, automated deployment, and rollback strategies.

  • Monitor production models for drift, accuracy degradation, and overall system health.

  • Develop REST APIs and integrate ML services into enterprise cloud applications.

  • Optimize models for latency, scalability, reliability, and cost.

  • Collaborate cross-functionally with Data Engineers, Software Engineers, Product Managers, and Clinical teams.

  • Provide technical leadership on AI/ML initiatives and ensure compliance with HIPAA, PHI, and PII standards.

What We're Looking For

  • 8+ years of professional software engineering and machine learning experience.

  • Strong healthcare industry background — this is a firm requirement.

  • Deep expertise across the full ML lifecycle: preprocessing, feature engineering, model development, calibration, deployment, monitoring, and maintenance.

  • Hands-on MLOps experience with strong Python and SQL skills.

  • Proficiency with distributed computing (Apache Spark) and Databricks in production environments.

  • Experience with at least one major cloud platform (Azure, AWS, or GCP).

  • Familiarity with MLflow, Feature Stores, Model Registries, Docker, and Git.

  • Experience building and integrating REST APIs; strong debugging and performance-tuning skills.

  • Working knowledge of HIPAA compliance requirements when handling sensitive healthcare data.

  • Nice to have: LLMs in production, RAG/prompt engineering, GenAI, Kubernetes, Scala, or managed ML platforms (Azure ML, SageMaker, Vertex AI).

  • US work authorization required; visa sponsorship is not available.

Compensation & Benefits

Hourly contract rate of $70–$75/hr on W2, equivalent to approximately $145,600–$156,000 annually. This is a contract (W2) engagement. Visa sponsorship is not available.

Location

Based in Palo Alto, CA. Work arrangement details to be confirmed with the hiring team.