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Entry Level Machine Learning Jobs in San Jose, CA

Apple

Machine Learning Engineer - Agentic AI

Sunnyvale, CA · On-site

$150K - $277K/yr

Description You will design and implement agentic systems built around large language models (LLMs) that extend beyond traditional machine learning pipelines. The work will require making tradeoffs ...

Muon Space

Software Engineer, Entry-Level

San Jose, CA

$142K - $169K/yr

... Entry-level software engineers are expected to bring significant skills and training, and then to ... Experience with mathematical optimization, machine learning, signal processing or advanced ...

Pwc

AI & GenAI Data Scientist - Manager

San Francisco, CA · On-site

$99K - $232K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Machine Learning information

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How much do entry level machine learning jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for entry level machine learning in San Jose, CA is $20.47, according to ZipRecruiter salary data. Most workers in this role earn between $18.32 and $22.26 per hour, depending on experience, location, and employer.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio. Internships, certifications, and participating in competitions like Kaggle can also improve your chances of entering the field without prior experience.
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What cities near San Jose, CA are hiring for Entry Level Machine Learning jobs?

Cities near San Jose, CA with the most Entry Level Machine Learning job openings:

Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in San Jose, CA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $42,575 per year, or $20.5 per hour.

HomeKit Machine Learning Engineer

Apple

San Francisco, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 683 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

The HomeKit team provides the foundation which enables an entire ecosystem of secure and intelligent connected home devices. Our mission is to create a scalable, distributed system that will transform how people interact with their home accessories. We are looking for a dedicated and passionate engineer to help advance our Home platform intelligence and elevate it to new heights. As a Machine Learning Engineer you will have an opportunity to be part of Smart Home focused ML innovation within Apple, initially focused on Applied ML for Computer Vision. The team is well positioned for strategic contributions in the short-term (on well-known Apple products) and in the long-term (on highly ambitious, high-risk, high-reward projects). This role has a strong focus on shipping ML-based features and products. You'll innovate in the entire end-to-end ML production pipeline. This includes but is not limited to; crafting creative approaches to datasets, model training, and on-device inference optimizations. Our ideal team member is fearless when it comes to trying new things and is willing to iterate on ideas. We value team members who can quickly prototype, iterating all the way to high-quality implementations.
Description
As a member of this team, you will use your background to:
- Develop features and models to improve the capabilities of systems that use machine learning
- Scale up model training, build data pipelines, and tuning to improve system performance
- Review and implement pioneering machine learning algorithms
- Build software that improves rate of experimentation
Minimum Qualifications
Bachelor's, Master's, or PhD or equivalent experience in Computer Science or a related field.
A strong curiosity, willingness to dive deep into unfamiliar problems, and an eagerness to learn and grow in a fast-evolving field.
Proficient in Python and deep learning frameworks like PyTorch, as well as familiarity with a language like Swift, C, C++ or Objective C.
Preferred Qualifications
Experience with training ML models including deep learning based models and model optimization.
Able to define metrics, evaluate ML models, and perform error analysis.
Familiar with recent advances in deep learning.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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