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Remote Full Stack Machine Learning Engineer Jobs in Santa Clara, CA

Omnissa

Staff Machine Learning Engineer

Mountain View, CA · On-site +1

$162K - $342K/yr

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems that power predictive analytics, personalization, automation, and intelligent platform behaviors.You ...

Vianai Systems

Full Stack Developer (Remote)

Palo Alto, CA · Remote

$110K - $160K/yr

As a full-stack developer, you would touch nearly every aspect of our business and work in cross ... Knowledge in Business Intelligence, Artificial Intelligence, and Machine Learning. Who We Are: We ...

Vianai Systems

Full Stack Developer

Palo Alto, CA · On-site +1

$110K - $160K/yr

As a full-stack developer, you would touch nearly every aspect of our business and work in cross ... Knowledge in Business Intelligence, Artificial Intelligence, and Machine Learning. Who We Are: We ...

Vianai Systems

Full Stack Developer

Palo Alto, CA · On-site +1

$110K - $160K/yr

As a full-stack developer, you would touch nearly every aspect of our business and work in cross ... Knowledge in Business Intelligence, Artificial Intelligence, and Machine Learning. Who We Are: We ...

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All JobsFull Stack Machine Learning Engineer JobsRemote Full Stack Machine Learning Engineer JobsRemote Full Stack Machine Learning Engineer Jobs in Santa Clara, CA

Remote Full Stack Machine Learning Engineer information

See Santa Clara, CA salary details

$52.3K

$158.3K

$223.7K

How much do remote full stack machine learning engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for remote full stack machine learning engineer in Santa Clara, CA is $158,280.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,400.00 and $185,600.00 per year, depending on experience, location, and employer.

What is a remote full stack machine learning engineer?

A Remote Full Stack Machine Learning Engineer is a professional who designs, develops, and deploys machine learning solutions while working remotely. They handle both the front-end and back-end aspects of machine learning projects, including data preprocessing, model building, API development, and integration with user interfaces or cloud platforms. This role requires expertise in programming, machine learning frameworks, cloud services, and web technologies, allowing them to build end-to-end AI-driven applications from anywhere in the world.

What are the key skills and qualifications needed to thrive as a remote full stack machine learning engineer?

To thrive as a Remote Full Stack Machine Learning Engineer, you need proficiency in programming languages (such as Python or JavaScript), a solid understanding of machine learning algorithms, experience with web development frameworks, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Docker, cloud computing platforms (AWS, GCP), and version control systems (Git) is essential. Strong problem-solving skills, self-motivation, and clear communication are crucial soft skills, especially in remote and cross-functional team environments. These combined skills ensure effective design, deployment, and integration of machine learning solutions in scalable web applications while maintaining productivity in a remote setting.

What are some common challenges faced by remote full stack machine learning engineers, and how can they be addressed?

Remote Full Stack Machine Learning Engineers often encounter challenges such as managing effective collaboration with cross-functional teams and ensuring smooth deployment of machine learning models into production environments. To address these, it's important to establish clear communication channels, regularly participate in virtual stand-ups, and use collaborative platforms such as GitHub and Slack. Additionally, staying organized with version control and thorough documentation helps maintain project transparency and ensures seamless handoffs between backend and frontend development. Proactively seeking feedback and scheduling regular check-ins with team members can further enhance productivity and integration within the team.

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

AspectRemote Full Stack Machine Learning EngineerRemote Data Scientist
Primary FocusDeveloping end-to-end machine learning applications, including backend, frontend, and model deploymentAnalyzing data, creating models, and generating insights without necessarily building full applications
Skills RequiredProgramming (Python, JavaScript), ML frameworks, web development, deployment toolsStatistics, data analysis, visualization, Python/R, SQL
Work EnvironmentCollaborates with developers, data engineers, and product teams in tech-driven companiesWorks with data teams, analysts, and business units in various industries

While both roles involve working with data and machine learning, a Remote Full Stack Machine Learning Engineer builds complete applications with integrated ML models, whereas a Remote Data Scientist focuses on data analysis and model creation without necessarily developing full applications.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Santa Clara, CA?

The most popular types of Full Stack Machine Learning Engineer jobs in Santa Clara, CA are:

What are popular job titles related to Remote Full Stack Machine Learning Engineer jobs in Santa Clara, CA?

For Remote Full Stack Machine Learning Engineer jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Remote Full Stack Machine Learning Engineer jobs in Santa Clara, CA look for?

The top searched job categories for Remote Full Stack Machine Learning Engineer jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Remote Full Stack Machine Learning Engineer jobs?

Cities near Santa Clara, CA with the most Remote Full Stack Machine Learning Engineer job openings:

Remote Full Stack Machine Learning Engineer jobs near you
Infographic showing various Remote Full Stack Machine Learning Engineer job openings in Santa Clara, CA as of June 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 42% Physical, 2% Hybrid, and 56% Remote job distribution, with an average salary of $158,280 per year, or $76.1 per hour.

Machine Learning Engineer - Remote

Palo Alto, CA • Remote

YO AI Labs
See more jobs at YO AI Labsexternal

$80 - $120/hr

Full-time

Posted 13 days ago

Job description

Senior Software Engineer

Job Type: Contractor (~15 hours/week)
Location: Remote

Job Summary

We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using Model Context Protocol (MCP) tools.

You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.

Key Responsibilities
  • Create reinforcement learning environments for software engineering tasks.
  • Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
  • Build deterministic verification systems and golden reference solutions.
  • Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
  • Develop realistic, reproducible software engineering scenarios.
  • Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
  • Document solutions and provide clear technical feedback.
Required Skills
  • Strong proficiency in Python 3, Java, Rust, C++, or TypeScript.
  • Strong understanding of algorithms and data structures.
  • Experience with bug fixing and debugging complex software issues.
  • Proven experience in feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication.
  • Strong attention to detail.
Preferred Qualifications
  • Experience working with large-scale or distributed codebases.
  • Familiarity with AI/ML systems is a plus but not required.
  • Experience with rigorous code reviews and software engineering best practices.
  • Experience working effectively in remote or cross-functional teams.
Hiring Process
  1. Submit an application and screening questions.
  2. Complete an AI interview (~30 minutes).
  3. Complete a technical assessment, if required.
  4. Hiring Manager review.
Compensation

Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.

Availability

Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.