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Graduate Machine Learning Engineer Jobs in California

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Machine Learning Engineer Location: San Jose, CA/Chicago, IL Duration: 18 months contract with a possible extension What You'll Do • Redesign and optimize PayPal's MLOps and decision platform for ...

The Opportunity Adobe is looking for a Machine Learning Engineer who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

As a Machine Learning Engineer, you will develop state-of-the-art AI intelligence solutions and collaborate with a team to enhance technology and drive innovation. Responsibilities : • Leverage ...

The Opportunity Adobe is looking for a Machine Learning Engineer who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the ...

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...

As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered features and workflows leveraging LLMs and modern AI techniques. You will collaborate closely with ...

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...

Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around ...

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Graduate Machine Learning Engineer information

See California salary details

$31.1K

$127.1K

$191K

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

As of Jun 20, 2026, the average yearly pay for graduate machine learning engineer in California is $127,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,200.00 and $153,000.00 per year, depending on experience, location, and employer.

What does a Graduate Machine Learning Engineer do?

A Graduate Machine Learning Engineer is an entry-level professional who designs, develops, and tests machine learning models and algorithms. They work with data scientists and engineers to preprocess data, train models, and deploy solutions to solve real-world problems. Their responsibilities often include coding in languages like Python, using libraries such as TensorFlow or PyTorch, and staying updated with the latest advancements in machine learning. This role serves as a starting point for a career in AI, providing hands-on experience in building and optimizing intelligent systems.

What are the key skills and qualifications needed to thrive as a Graduate Machine Learning Engineer, and why are they important?

To thrive as a Graduate Machine Learning Engineer, you need a solid foundation in computer science, mathematics (especially statistics and linear algebra), and proficiency in programming languages like Python, often supported by a relevant degree. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), version control systems (like Git), and experience with cloud platforms or data management tools are typically expected. Strong analytical thinking, problem-solving abilities, and effective communication help you collaborate and translate complex concepts into practical solutions. These skills and qualities are crucial for developing robust models, integrating them into real-world applications, and contributing effectively to multidisciplinary teams.

What are some common challenges faced by Graduate Machine Learning Engineers during their first year, and how can they overcome them?

Graduate Machine Learning Engineers often encounter challenges such as bridging the gap between academic knowledge and real-world application, working with large or messy datasets, and learning to collaborate within cross-functional teams. Adapting to production-level code standards and understanding existing codebases can also be demanding. To overcome these hurdles, it's helpful to seek mentorship from experienced colleagues, actively participate in code reviews, and invest time in learning best practices for data preprocessing and model deployment. Embracing continuous learning and open communication will ease the transition into the professional environment.

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

AspectGraduate Machine Learning EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related field; some internshipsBachelor's or Master's in Statistics, Data Science, or related field; often with experience
Work EnvironmentDeveloping ML models, coding, testing algorithmsAnalyzing data, creating visualizations, deriving insights
Employer & Industry UsageTech companies, startups, research labsFinance, healthcare, tech, consulting firms

While both roles involve working with data and algorithms, Graduate Machine Learning Engineers focus on developing and deploying machine learning models, often requiring coding and technical skills. Data Scientists analyze data to extract insights and inform decisions. The roles overlap in skills but differ in primary responsibilities and focus areas.

What job categories do people searching Graduate Machine Learning Engineer jobs in California look for? The top searched job categories for Graduate Machine Learning Engineer jobs in California are:
What cities in California are hiring for Graduate Machine Learning Engineer jobs? Cities in California with the most Graduate Machine Learning Engineer job openings:
Infographic showing various Graduate Machine Learning Engineer job openings in California as of June 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $127,083 per year, or $61.1 per hour.
Machine Learning Engineer

Full-time

Posted 3 days ago


Job description

Job Summary:
General Atomics Aeronautical Systems, Inc. (GA-ASI) is a world leader in remotely piloted aircraft and tactical reconnaissance radars. They are seeking a Machine Learning Engineer to develop and deploy autonomous systems for unmanned aerial systems, working on algorithms and improving product performance.
Responsibilities:
• Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms of limited scope.
• In product/systems improvement projects, uses machine language and statistical modeling techniques to include but not limited to decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy.
• In both theoretical development environments and specific product design, implementation and improvement environments, uses programming language and technologies to translate algorithms and technical specifications into code.
• Completes programming and implements efficiencies, performs testing and debugging.
• Completes documentation and procedures for installation and maintenance.
• Applies deep learning technologies to give computers the capability to visualize, learn and respond to situations of limited scope.
• Lead technical teams and scope challenging projects into executable sprints.
• Drive code reviews to help team adhere to general DevSecOps and MLOps best practices.
• Have a growth mindset and be comfortable in a setting where milestones shift often due to customer preferences or technology evolution.
• Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience.
• Interface with external vendors and partners to integrate their technology into the team’s autonomy stack.
• Maintains the strict confidentiality of sensitive information.
• Performs other duties as assigned.
• Responsible for observing all laws, regulations and other applicable obligations wherever and whenever business is conducted on behalf of the Company. Expected to work in a safe manner in accordance with established operating procedures and practices.
Qualifications:
Required:
• Typically requires a bachelors or master's degree in computer science, engineering, mathematics, or a related technical discipline from an accredited institution and two or more years of machine learning experience with a bachelors degree. May substitute equivalent machine learning engineer experience in lieu of education.
• Must have an understanding of machine learning concepts, principles, and theory.
• Demonstrates the ability to follow and apply advanced machine learning knowledge, adapt cutting edge standard techniques, and utilize the required diagnostics, tools and equipment, while ensuring safety and regulatory compliance.
• Experience in developing and leading scalable software architectures from scratch.
• Experience in optimizing AI models to meet edge processing requirements.
• Strong coding skills in Java, Java Script, C/C++, Python.
• Experience in AI frameworks such as Tensorflow and pyTorch.
• Excellent verbal and written communication skills.
• Must be able to architect, design, and develop complex software.
• Technical expertise in the application of engineering principles, concepts, theory, and practice as well as project management and leadership skills including organizing, planning, scheduling, and coordinating workloads to meet established deadlines or milestones.
• Active membership and participation in relevant conference and professional society organizations.
• Demonstrated recent history of academic quality publications in the area of AI/ML and autonomy.
• Must be able to understand new concepts quickly and apply them accurately throughout an evolving environment.
• Strong communication, computer, and interpersonal skills are required to enable an effective interface with other professionals, to produce appropriate documentation, and to present results to a limited internal audience.
• Must be able to work both independently and on a team.
• Able to work extended hours as required.
• Customer focused, must be able to work on a self-initiated basis and in a team environment, and able to work extended hours and travel as required.
• Ability to obtain and maintain a DoD security clearance is required.
Company:
General Atomics Aeronautical Systems is an engineer, researcher and developers of advanced remotely piloted aircraft and systems. Founded in 1993, the company is headquartered in Poway, USA, with a team of 5001-10000 employees. The company is currently Late Stage.