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Entry Level Machine Learning Engineer Jobs in California

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Apple

Machine Learning Engineer

San Diego, CA

$139.50K - $258.10K/yr

Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...

Adobe, Inc.

Machine Learning Engineer

San Jose, CA · On-site

$151.80K - $265.35K/yr

As a Sr. Machine Learning Engineer, you will combine hands-on engineering with architectural leadership to design and implement reasoning systems, tool orchestration, and multimodal integrations ...

Apple

Machine Learning Engineer

Cupertino, CA

$147.40K - $272.10K/yr

Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123.10K - $169.10K/yr

They are seeking a Senior Machine Learning Engineer to develop and maintain machine learning infrastructure, particularly for cash advance underwriting models and other applications, while ...

Aven

Machine Learning Engineer

Campbell, CA · On-site

We are looking for Machine Learning Engineers who have built product models from idea to delivery. You are passionate about digging into data, cleaning it, analyzing it, generating ideas, and ...

SAP

Machine Learning Engineer

Palo Alto, CA

Machine Learning Engineer What you'll build We are seeking a motivated and curious Machine Learning Engineer to help build intelligent systems that power large-scale AI and large language model (LLM ...

SAP

Machine Learning Engineer

Palo Alto, CA · On-site

Machine Learning Engineer What you'll build We are seeking a motivated and curious Machine Learning Engineer to help build intelligent systems that power large-scale AI and large language model (LLM ...

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Entry Level Machine Learning Engineer information

See California salary details

$29.6K

$68.5K

$116.5K

How much do entry level machine learning engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for entry level machine learning engineer in California is $68,454.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,800.00 and $77,500.00 per year, depending on experience, location, and employer.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.
More about Entry Level Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in California? The most popular types of Machine Learning Engineer jobs in California are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in California? For Entry Level Machine Learning Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in California look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in California are:
What cities in California are hiring for Entry Level Machine Learning Engineer jobs? Cities in California with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in California as of May 2026, with employment types broken down into 1% Internship, 94% Full Time, 3% Part Time, 1% Contract, and 1% Nights. Highlights an 76% Physical, 3% Hybrid, and 21% Remote job distribution, with an average salary of $68,454 per year, or $32.9 per hour.
Machine Learning Engineering Intern

Machine Learning Engineering Intern

Qeexo, Co.

San Clemente, CA • On-site

$25/hr

Full-time

Posted 14 days ago

Job description

Machine Learning Engineer Intern TDK SensEI San Clemente, CA

**This position is for our San Clemente, CA office - only apply if you are based there or willing to relocate**

At TDK SensEI, we are transforming how industrial customers utilize and interact with sensor data. We specialize in developing advanced AI solutions capable of running directly on edge devices. By processing data locally, TDK SensEI enhances real-time decision-making, privacy, security, and cost efficiency. Our offerings include automated machine learning tools, AI-powered condition-based monitoring systems, and various sensor devices optimized for low latency and power consumption. Collaborating with leading global companies, we empower teams to effortlessly devise and implement machine learning solutions for industrial applications, all without the need for coding.

We are looking for a machine learning intern who loves working with sensor data, loves developing novel algorithms, and has strong curiosity about developing new GenAI-based ML applications. You will be working with a highly capable team of machine learning engineers and software engineers and will have the opportunity to make a meaningful impact on important new product development.

As a Machine Learning Engineer Intern, your responsibilities will include:

1. Assist in Model Development: Collaborate with senior engineers to develop and train machine learning models tailored for edge devices.

2. Data Collection and Preprocessing: Gather and preprocess data from various sensors and sources to ensure high-quality inputs for AI models.

3. Prototype Development: Develop and test prototypes for new Gen AI-based use cases, ensuring they meet performance and reliability standards.

4. Performance Evaluation: Conduct experiments to evaluate the performance of AI models and edge solutions, identifying areas for improvement.

5. Collaboration: Work closely with cross-functional teams, including machine learning and software engineers, to integrate AI solutions into prototype systems.

Ideal Candidate

. Signal processing and machine learning (most likely in EE major)

. Computer vision (most likely in CS major)

. Language model (most likely in CS major)

Deep knowledge of statistical and machine learning approaches and problem domains

Machine Learning/Computer Science/Electrical Engineering background with strong coding ability and proficiency with Python or other OOP language

Proven success with multiple ML/AI/classification projects (research papers, open-source implementations, etc.)

Expertise in one or more specific areas of research: automated machine learning, anomaly detection, condition monitoring, predictive maintenance, neural nets, deep learning, signal processing, digital imaging, ensemble learning, and system identification

Experience working with GenAI applications

Comfortable working in a terminal environment, writing scripts (Bash/Python) to process data and implement algorithms

Skills & Requirements:

Master's or PhD student

Python or other modern OOP language (proficient)

Data Structures and Algorithms (proficient)

Deep Learning (proficient)

Data Structures and Algorithms (familiar)

Experience with Docker and AWS (familiar)

US Work Authorization required

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About Qeexo

Sourced by ZipRecruiter

Industry

It services

Company size

1 - 10 Employees

Headquarters location

Mountain View, CA, US

Year founded

2012

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