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Junior Machine Learning Jobs in California (NOW HIRING)

Intuitive

Staff Machine Learning Engineer

Sunnyvale, CA · On-site

Mentor junior engineers and research scientists; establish best practices for experiment tracking ... machine learning, probabilistic modeling, or 3D scene understanding. * 5+ years of post-Ph.D. or 7+ ...

Intuitive

Staff Machine Learning Engineer

Sunnyvale, CA · On-site

Mentor junior engineers and research scientists; establish best practices for experiment tracking ... machine learning, probabilistic modeling, or 3D scene understanding. * 5+ years of post-Ph.D. or 7+ ...

Kiddom

Senior Machine Learning Engineer

San Francisco, CA · On-site

$175K - $250K/yr

Coach and mentor junior ML engineers and data scientists, fostering technical and professional growth. Who you are * Have 5+ years of industry experience applying machine learning to solve real-world ...

ASAPP

Lead Machine Learning Engineer

Mountain View, CA · On-site

$170K - $190K/yr

We are looking for a Machine Learning Engineer to help build and evaluate the core intelligence ... Demonstrate proficiency in the technical mentorship of junior and mid-level engineers, driving the ...

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Junior Machine Learning information

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

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

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What is the difference between Junior Machine Learning vs Data Scientist?

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What are the most commonly searched types of Machine Learning jobs in California?

The most popular types of Machine Learning jobs in California are:

What are popular job titles related to Junior Machine Learning jobs in California?

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

What job categories do people searching Junior Machine Learning jobs in California look for?

The top searched job categories for Junior Machine Learning jobs in California are:

What cities in California are hiring for Junior Machine Learning jobs?

Cities in California with the most Junior Machine Learning job openings:

Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in California as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution.

Senior Machine Learning Engineer

Berkeley, CA • On-site, Remote

The Voleon Group
Investment Management and Consulting Services • 11 - 50 employees
Learn more about The Voleon Groupexternal

$290K - $395K/yr

Full-time

Re-posted 26 days ago

Key responsibilities

  • Partner with research staff to design, implement, and productize machine learning models for quantitative trading strategies

  • Develop and maintain data pipelines, including data ingestion, feature engineering, validation, and quality monitoring

  • Translate research prototypes and ideas into production-ready, well-tested code

Job description

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future.
Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.
As a Senior Machine Learning Engineer on one of Voleon's Research teams, you will partner directly with research staff to advance our quantitative trading strategies. You will translate novel research ideas into production-quality code, build and maintain the data pipelines and modeling infrastructure that underpin our strategies, and apply your own strong mathematical intuition to solve open-ended technical challenges.
This role lives at the boundary of research and engineering. You will be expected to understand the statistical and mathematical concepts your research partners work with, contribute meaningfully to technical discussions about model design and evaluation, and ensure that the resulting systems are performant, reliable, and maintainable. You will work at the intersection of Computer Science, Mathematics, and Statistics - building high-performance tools that enable world-class research while maintaining a high engineering standard.
Responsibilities
  • Partner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategies
  • Develop and maintain complex data pipelines, including data ingestion, feature engineering, validation, and quality monitoring
  • Translate research prototypes and novel ideas into performant, well-tested, production-ready code
  • Build extensible tools and frameworks that accelerate the model development and experimentation lifecycle
  • Supervise, understand, and remediate subtle data quality issues across both research and production environments
  • Proactively lead projects from requirements through delivery, making autonomous decisions about scope, dependencies, and trade-offs, with an emphasis on long-term maintainability
  • Coordinate and contribute to deployment efforts while guiding junior engineers and researchers; align with research and engineering stakeholders on ownership, execution, and prioritization
  • Foster engineering consistency, standards, and best practices within Research

Requirements
  • Bachelor's degree (or higher) in Computer Science, Applied Mathematics, Statistics, or a related quantitative field
  • 5+ years of professional software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design)
  • Demonstrated mathematical maturity - comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability
  • Deep proficiency in Python; experience with R and/or C/C++ is a strong plus
  • Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar)
  • Proven experience building or maintaining machine learning systems in a distributed computing environment
  • Proficiency developing in a Linux environment with attention to performance, correctness, and reproducibility
  • Exceptional attention to detail, particularly when working with imperfect or heterogeneous data
  • Strong verbal and written communication skills, and the ability to collaborate effectively with researchers whose primary expertise is not software engineering

Preferred Qualifications
  • Experience with experiment management, model evaluation pipelines, or ML workflow orchestration
  • Familiarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training)
  • Experience with performance profiling and optimization of numerical or modeling code
  • Prior exposure to financial data, time-series analysis, or quantitative research environments

"Friends of Voleon" Candidate Referral Program
If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program.
Equal Opportunity Employer
The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
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About Voleon Group

Sourced by ZipRecruiter

Industry

Investment management and consulting services

Company size

11 - 50 Employees

Headquarters location

Berkeley, CA, US

Year founded

2007

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