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Executive Full Stack Machine Learning Engineer Jobs in California

Apple

Sr. Machine Learning Engineer, Siri Global

Cupertino, CA · On-site

$151.10K - $199.20K/yr

We are particularly interested in "full-stack" machine learning engineers with strong experience in ... and executives. Software engineering experience with both server-based and client-side (e.g. on ...

HADRIAN

Machine Learning Engineer

Los Angeles, CA · On-site

$160K - $250K/yr

By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how ... As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ...

HADRIAN

Machine Learning Engineer

Los Angeles, CA · On-site

$160K - $250K/yr

By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how ... As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a ... We offer a full comprehensive benefits package including medical, dental and vision. Employees ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a ... We offer a full comprehensive benefits package including medical, dental and vision. Employees ...

Aquabyte

Machine Learning Engineer

San Francisco, CA · On-site

$130K - $170K/yr

... stack. Above all, Aquabyte is a customer-driven company. Our product development is dictated by the ... The role As a Machine Learning Engineer you will be responsible for developing Machine Learning ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Familiarity with data processing stacks such as Spark and Airflow. * Experience with multi-node GPU ...

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Executive Full Stack Machine Learning Engineer information

What is the difference between Executive Full Stack Machine Learning Engineer vs Data Scientist?

AspectExecutive Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Engineering, or related; often requires experience in ML and full stack developmentBachelor's/Master's in Data Science, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops end-to-end ML solutions, integrates backend and frontend, collaborates with engineering teamsAnalyzes data, builds models, visualizes insights, often in research or analytics teams
Industry UsageUsed in tech companies, startups, and enterprises deploying ML productsCommon in research institutions, analytics firms, and data-driven organizations

The Executive Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, combining software engineering and data science skills. In contrast, Data Scientists primarily analyze data and develop models without necessarily handling full stack development. Both roles require strong technical credentials but differ in scope and daily tasks.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in California? The most popular types of Full Stack Machine Learning Engineer jobs in California are:
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Executive Full Stack Machine Learning Engineer jobs near you
Fullstack Machine Learning Engineer, Infrastructure

Fullstack Machine Learning Engineer, Infrastructure

Tesla

Palo Alto, CA • On-site

Full-time

Posted 20 days ago

Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers

Job description

Job Summary:
Tesla is driving forward the next generation of robots, electric vehicles, and energy products. They are seeking a skilled Full-Stack Machine Learning Engineer to develop in-house tools that automate complex processes and empower engineers to design faster and operate more efficiently, directly impacting Tesla's mission of sustainable energy.
Responsibilities:
• Design, develop, test, deploy, scale, and maintain user-friendly web applications and tools that automate existing design workflows and visualize machine learning experiments and models
• Combine multiple data-sources and leverage millions of data points to build robust and scalable end-to-end learning-based systems. This includes training and evaluation code in Python to back-end and front-end work in JavaScript
• Collaborate with cross-functional teams to integrate software systems into Tesla's ecosystem, ensuring seamless deployment and operation
• Build dashboards that provide real-time insights into performance, progress, and key metrics for engineers and leadership
• Proactively identify and resolve performance bottlenecks related to infrastructure, memory, and runtime efficiency
• Present progress at project milestones to stakeholders and cross-functional teams
Qualifications:
Required:
• Degree in Computer Science or equivalent experience
• Proficiency in writing production quality code in Python, and experience with any major machine learning framework
• Experience in optimization techniques and time-series forecasting
• Strong knowledge of the React ecosystem, including familiarity with major solutions for State Management (Redux Toolkit, Zustand, MobX), Styling (Tailwind CSS, Styled Components, MUI), and Testing (Jest, Vitest, Playwright)
• Solid understanding of web development best practices, security principles, design patterns, scalability principles, and component‑reuse strategies
• Experience deploying services on Kubernetes or other big data technologies and setting up CI/CD pipelines
• Experience implementing identity management protocols such as OAuth2, OIDC, and JWT, with attention to preventing vulnerabilities (OWASP Top 10, XSS, CSRF)
• Excellent interpersonal, communication, and collaboration skills
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Tesla employees say

Pay

Benefits

Hours and flexibility

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