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Junior Machine Learning Jobs in California (NOW HIRING)

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

... junior engineers through their journey to become better. Responsibilities * Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting ...

Hive

Machine Learning Manager

San Francisco, CA

$180K - $250K/yr

... junior engineers through their journey to become better. Responsibilities * Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting ...

Qubeaxis

Machine Learning Engineer

San Francisco, CA · On-site

$130 - $180/hr

Job Title Machine Learning Engineer Job ID 20985 Location Work Mode Onsite About the Team Our ML ... We run a structured onboarding programme for junior hires including a dedicated mentor, a 90-day ...

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)

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

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 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.

Machine Learning Engineer

Ascent Developer Solutions

Los Angeles, CA

Full-time

Re-posted 20 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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