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Graduate Machine Learning Engineer Jobs in California

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

... machine learning engineers. We are looking for developers who are excited about staying at the ... You have an undergraduate or graduate degree in computer science or similar technical field, with ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Apple

Machine Learning Engineer

Santa Clara, CA · On-site

Our team comprises a diverse range of backgrounds, including applied machine learning engineers with a focus on ML and LLM, and experienced distributed systems engineers. As such, we are seeking ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

... machine learning engineers. We are looking for developers who are excited about staying at the ... You have an undergraduate or graduate degree in computer science or similar technical field, with ...

General Atomics

Machine Learning Engineer

Poway, CA · On-site

We have an exciting opportunity for a Machine Learning Engineer in Poway, CA. The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous ...

Lyft

Machine Learning Engineer

San Francisco, CA · On-site

Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the ...

Lyft

Machine Learning Engineer

San Francisco, CA · On-site

Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the ...

NR Consulting

Machine Learning Engineer

Fremont, CA · On-site

NR Consulting is a company focused on innovative technology solutions, and they are seeking a Machine Learning Engineer to develop and deploy lightweight machine learning models for edge AI ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to core technology and product features.

Machina Labs

$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 ...

Latent

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

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 ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

The Machine Learning Engineer will play a central role in building the core technology for training, evaluating, and deploying interpretable frontier AI systems, contributing to tools, infrastructure ...

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Showing results 21-40

All JobsGraduate Machine Learning Engineer JobsGraduate Machine Learning Engineer Jobs in California

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 Sep 10, 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 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 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 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 are popular job titles related to Graduate Machine Learning Engineer jobs in California?

For Graduate Machine Learning Engineer jobs in California, the most frequently searched job titles are:

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:

Graduate Machine Learning Engineer jobs near you
Infographic showing various Graduate Machine Learning Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,083 per year, or $61.1 per hour.

Machine Learning Engineer

Los Angeles, CA • On-site

Ascent Developer Solutions
See more jobs at Ascent Developer Solutionsexternal

Full-time

Re-posted 8 days ago

Job description

ROLE SUMMARY 

The Machine Learning Engineer is a major contributor in driving our company's innovation and data-driven decision-making. By harnessing advanced analytics, machine learning, and big data technologies, this role directly impacts strategic business outcomes, revealing actionable insights and predicting trends that shape the future of our operations. Embedded at the intersection of data and strategy, the Data Scientist empowers the organization to navigate complex challenges, optimize performance, and unlock new growth opportunities. 

ESSENTIAL DUTIES 

Data and analysis 

  • Analyze public records and other real estate data using NLP and machine learning techniques to identify patterns and cluster entities. 
  • Develop methods for evaluating and selecting large language models (LLMs) for deployment. 
  • Build predictive models to identify potential borrowers, likelihood of default, and quality/valuations of properties for lending activities. 
  • Identify new business opportunities through tracking competitor trends and keeping management aware of developer lending market trends and insights. 
  • Assist in fostering a culture of test & learn within the company. 

Leadership  

  • Serve as analytics consultant to a broad variety of line-of-business teams. 
  • Partner with technology teams on product changes and impacts on data/performance. 
  • Mentor junior analysts on various data science techniques. 

 QUALIFICATIONS 

  • Bachelor's degree in quantitative field. 
  • 5-7 years of experience in analytical or consulting roles. 
  • Strong data science skills with AI/ML related Python libraries such as PyTorch, TensorFlow, and Keras. Conceptual knowledge of LLM's. 
  • Strong knowledge of statistics, hypothesis testing, and setting up experiments. 
  • Must have deployed several models to production. 
  • Exposure to data engineering skills. 
  • Strong communication and partnership skills, effective cross-department collaboration skills. 
  • Self-starter who can work under limited supervision. 
  • Mentoring skills to help develop junior analysts. 

WORK ENVIRONMENT 

  • This role works on-site from Ascent's Encino office 2 days per week 

THE PAY 

Salary range is $130,000-$150,000 per year, with a discretionary bonus of 20% per year. 

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