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Junior Machine Learning Jobs in California (NOW HIRING)

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you ...

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of data-driven and ML-powered solutions for semiconductor R&D, test, and operations teams. In this role ...

Machine Learning Engineer LeanData helps the world's fastest-growing companies automate, simplify ... Experience leading and mentoring a team of junior engineers while providing technical guidance and ...

Sr Machine Learning Engineer

Thousand Oaks, CA · On-site +1

$158K - $200K/yr

... junior machine learning engineers and data scientists in a formal or matrixed fashion. May telecommute. Requirements:Bachelor's degree (or foreign equivalent) in Computer Science, Statistics ...

... junior machine learning engineers and data scientists in a formal or matrixed fashion. May telecommute. Requirements: Bachelor's degree (or foreign equivalent) in Computer Science, Statistics ...

... 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 ...

... 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 ...

Mentor junior team members and share technical expertise to elevate team capabilities We'd love to chat if you have: * Proven experience building and deploying machine learning models in production ...

Senior Machine Learning Engineer

San Jose, CA · On-site

$143K - $189K/yr

... junior team members and share technical expertise to elevate team capabilities Qualifications : Required : • Proven experience building and deploying machine learning models in production ...

Senior Machine Learning Engineer

San Jose, CA · On-site

$122K - $168K/yr

... junior team members and share technical expertise to elevate team capabilities Qualifications : Required : • Proven experience building and deploying machine learning models in production ...

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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 engineers make $500,000?

Senior engineers in fields like software, data engineering, or specialized roles such as machine learning engineers can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant funding.

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.

Can I get into AI with no experience?

Junior Machine Learning roles typically require some foundational knowledge of programming, mathematics, and data analysis. While prior experience is often preferred, beginners can enter the field by learning relevant skills through online courses, tutorials, and projects, and by gaining familiarity with tools like Python and machine learning frameworks. Building a portfolio and obtaining certifications can also improve chances of entry-level employment.

Which 3 jobs will survive AI?

Junior Machine Learning roles are likely to persist as they require specialized knowledge, critical thinking, and domain expertise that AI cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and AI system trainers, are also expected to remain in demand. Continuous learning and adapting to new tools will be essential for these roles to stay relevant.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, extensive expertise, and may include stock options or bonuses as part of compensation packages.

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

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 cities in California are hiring for Junior Machine Learning jobs? Cities in California with the most Junior Machine Learning job openings:

Machine Learning Engineer

Advantest

San Jose, CA • On-site

Full-time

Posted 18 days ago


Job description

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you'llcontribute to building predictive models, conducting statistical analyses, andassistingin the development of lighttomoderate data pipelines that help transform complex semiconductor datasets into actionable insights.

This position is ideal for a recent graduate with strong foundational ML skills whoiseager to learn, collaborate, and grow in a fastpaced, technically rich environment.You'llwork alongside experienced engineers, data scientists, and domain experts while gaining handson experience across the ML lifecycle-from data preparation to model deployment

Key Responsibilities

Machine Learning & Advanced Analytics

  • Develop and evaluate ML models (e.g., classification, anomaly detection, regression, timeseries analysis).
  • Perform feature engineering andexploratorydata analysis on semiconductor datasets.
  • Contribute to model deployment workflows in collaboration with MLdata scientists, followingMLOpsbest practices.
  • Assistin implementing model monitoring, retraining workflows, and documentation.
  • Experiment with modern analytics techniques, including LLMbased or generativeAI methods, under guidance from senior team members.

Data Engineering & Pipeline Support

  • Help build and maintain ETL/ELT workflows that prepare data for analysis and modeling.
  • Support data quality checks, versioning, and data validation tasks.
  • Work with cloudand onpremtools to help ensure data accessibility for ML applications.

CrossFunctional Collaboration

  • Work with semiconductor engineers and data scientists to translate domain challenges into analytical tasks.
  • Support the creation of dashboards, reports, and visualizations that communicate insights clearly.
  • Learn and apply semiconductorspecific data concepts with the support of senior mentors.