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Junior Machine Learning Jobs in California (NOW HIRING)

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Provide guidance and mentorship to junior engineers, fostering a culture of learning and growth ... Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch)

Cotality

Senior Machine Learning Scientist

Irvine, CA · Hybrid

Mentor junior data scientists and machine learning engineers, providing technical guidance and driving knowledge sharing across the team. * Documentation: Create and maintain rigorous documentation ...

Petco

Sr. Engineer, AI Platform Engineering

San Diego, CA · On-site

$107K - $147K/yr

May provide mentorship and guidance to junior machine learning engineers. * Conduct training sessions to share knowledge and best practices within the team. ML Ops Best Practices: * Design and ...

New

Hive

Senior Machine Learning Engineer

San Francisco, CA · On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best ... Provide mentorship to and help onboard junior ML engineers * Collaborate cross-functionally with ...

Hive

Senior Machine Learning Engineer

San Francisco, CA · On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best ... Provide mentorship to and help onboard junior ML engineers * Collaborate cross-functionally with ...

TetraMem Inc

Senior Machine Learning Engineer

San Jose, CA · On-site

$200K - $280K/yr

Provide technical leadership and mentorship to junior engineers. * Publish research findings ... Strong hands-on experience in machine learning, with a focus on edge AI, on-device inference, and ...

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All JobsMachine Learning JobsJunior Machine Learning JobsJunior Machine Learning Jobs in California

Junior Machine Learning information

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 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 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 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 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 August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Machine Learning Engineer

Kikoff

San Francisco, CA • On-site

$123K - $169K/yr

Full-time

Posted 20 days ago

Job description

Kikoff: The Fintech Powering Financial Security at Scale
Kikoff is a profitable, pre-IPO fintech company on a mission to empower everyone to achieve financial security. With record revenue growth in 2025 and a unicorn valuation, we've built a suite of products that help millions of people build credit, access liquidity, and save money.
We're scaling fast. Join us if you want to build something meaningful and help millions of people move forward financially.
Why Kikoff:
This is a consumer fintech startup, and you will be working with serial entrepreneurs who have built strong consumer brands and innovative products. We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships. Yes, you can build an exciting business AND have real-life real-customer impact.
We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on developing and maintaining machine learning infrastructure and operations, particularly for our cash advance underwriting model and other machine learning use cases. The ideal candidate will have a strong background in software development, machine learning, and data engineering, with experience in deploying scalable ML models in production environments.
Key Responsibilities:
  • ML Infrastructure and Operations: Design, build and maintain the infrastructure required for optimal extraction, transformation, and loading of data from various sources. Develop and manage data pipelines and workflows for machine learning models.
  • Model Development and Deployment: Design, develop, and implement machine learning models for underwriting and other financial service applications. Ensure models are robust, scalable, and maintainable.
  • Collaboration: Work closely with data scientists, software engineers, and product managers to integrate machine learning models into production systems. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Performance Monitoring: Monitor and evaluate the performance of deployed models, ensuring they meet the desired accuracy and efficiency metrics. Implement processes for continuous improvement and optimization of models.
  • A/B Testing and Experimentation: Design and implement experiments to optimize models and ensure they align with business goals.
  • Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of learning and growth within the team.

Qualifications:
  • Educational Background: Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field. Advanced degree preferred.
  • Experience: Minimum of 3 years of experience in machine learning engineering, with a proven track record of deploying ML models in production environments.
  • Technical Skills:
    • Proficiency in programming languages such as Python or Ruby.
    • Strong understanding of data structures, algorithms, and software design principles.
    • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch).
    • Familiarity with MLOps practices and tools for continuous integration and deployment of ML models.
    • Experience with cloud services (e.g., AWS, GCP) and containerization technologies (e.g., Docker, Kubernetes).
  • Analytical Skills: Strong problem-solving skills with the ability to analyze complex data sets, apply advanced data science techniques, and derive actionable insights. Proficient in building predictive models, performing statistical analysis, and utilizing machine learning algorithms to identify trends, patterns, and opportunities for optimization.
  • Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

What we're like:
- Scrappy. We had a product goal and put out the MVP, collecting our first users with steady growth via paid channels in four months. We don't cut corners when we know we'll need them but we don't build things without that need. We don't like inefficiency but we dislike operationalizing one-off tasks even more.
- Risk-oriented. Everything has risk, but a mature team knows how to make these tradeoffs. That's why we built the MVP fast--because time is your most valuable asset and is practically fungible with money in the startup world.
- Data-obsessed. We all look at data and pull it, and we believe that understanding the mechanics can yield valuable insights. Complex systems require elegant, not just simple solutions. You absolutely need to be interested in data if you want to leverage your knowledge of systems.
- Lucky. That's how we look at this journey so far. From our timing of fundraising, to the circumstances in which we came together, to the initial product traction we're getting, there's no other word to describe it. We are grateful you are reading this, and we know that if you're meant to be with us on this journey, then we will see you soon.
Base Range
$244,000-$292,000 USD
Equal Employment Opportunity Statement
Kikoff Inc. is an equal opportunity employer. We are committed to complying with all federal, state, and local laws providing equal employment opportunities and considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Please reference the following for more information.

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