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Entry Level Machine Learning Engineer Jobs in Pleasanton, CA

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

MM International

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

Adobe, Inc.

Machine Learning Engineer

San Jose, CA · On-site

Machine Learning Engineer The Opportunity Join Adobe and be at the forefront of driving digital transformation. As a Machine Learning Engineer, you will play a key role in developing machine learning ...

Adobe

Machine Learning Engineer

San Jose, CA · On-site

Adobe is at the forefront of driving digital transformation and is seeking a Machine Learning Engineer to develop machine learning models and algorithms. The role involves collaborating with multi ...

Gotion Inc.

Machine Learning Engineer

Fremont, CA · On-site

They are seeking a highly motivated Machine Learning Engineer to design and implement machine learning models for advanced battery products, collaborating with cross-disciplinary teams to address ...

Advantest

Machine Learning Engineer

San Jose, CA

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 ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

Adobe

Machine Learning Engineer

San Jose, CA

As a Machine Learning Engineer, you will play a key role in developing machine learning models and algorithms. Our team is dedicated to solving complex business challenges through innovative machine ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

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 ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA

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 ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine learning research into scalable, production-ready solutions. You will collaborate closely with cross ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

... machine learning/deep learning systems, computer vision, graphics, computational imaging applications.Experience with Pytorch. MS/PhD in computer vision, electrical, optical or computer engineering ...

Advantest

Machine Learning Engineer

San Jose, CA · On-site

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 ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$147.40K - $272.10K/yr

... engineers across Apple.","responsibilities":"Design, train and tune machine learning algorithms, support camera architects to drive innovative solutions for imaging and sensing challenges, and ...

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 ...

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 ...

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Entry Level Machine Learning Engineer information

See Pleasanton, CA salary details

$33.4K

$77.2K

$131.3K

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 Pleasanton, CA is $77,193.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,300.00 and $87,400.00 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 Pleasanton, CA? The most popular types of Machine Learning Engineer jobs in Pleasanton, CA are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Pleasanton, CA look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Pleasanton, CA are:
What cities near Pleasanton, CA are hiring for Entry Level Machine Learning Engineer jobs? Cities near Pleasanton, CA with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you

Machine Learning Engineer

Winaxis

Fremont, CA • On-site

Contractor

Posted 11 days ago

Job description

Title: Machine Learning Engineer

Location: Fremont, CA (Local) Onsite interview

Duration: 12+ Mos  

H1B

Only h1 candidate

About the Role:

Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design, develop, and implement critical machine learning models supporting factory and warehouse operations. You will transform ambiguous problem statements into robust end-to-end solutions using a variety of machine learning techniques and tools, including supervised learning, convolutional neural networks, and modern frameworks such as PyTorch and Pandas.

You will collaborate closely with partners in production, process, controls, and quality to deliver solutions for the most challenging problems in our operations. Your work will involve evaluating and deploying models in production environments, ensuring rapid and reliable alerting systems, and addressing operational issues as they arise. You must be adept at handling diverse, heterogeneous datasets that span multiple modalities, including images, multi-spectral sensor outputs, voice, text, and tabular data.

Responsibilities

Design, develop, and deploy machine learning models for factory and warehouse environments.

Collaborate with cross-functional teams to identify, define, and solve high-impact operational challenges.

Build and maintain end-to-end machine learning pipelines, from data collection and preprocessing to model deployment and monitoring.

Evaluate and compare models using statistical methods to ensure optimal performance and feasibility.

Ensure robust alerting and monitoring systems are in place for deployed models to address issues rapidly.

Work with diverse datasets, integrating multiple data types such as images, sensor data, voice, text, and tabular information.

Write clean, modular, and sustainable code to translate research ideas into production-ready solutions.

Minimum Requirements

In-depth knowledge of Python for high-performance, data-intensive applications.

Proficiency with at least one modern deep learning framework (e.g., PyTorch, Jax, TensorFlow).

Expertise in one or more of the following areas: computer vision, large language models, recommender systems, or operations research.

Foundational knowledge of statistics for model comparison and performance assessment.

Real-world experience deploying and maintaining machine learning solutions in production environments.

Passion for clean, sustainable, and modular code to bring research concepts to practical implementation.

Preferred Qualifications

Experience working in manufacturing, industrial automation, or warehouse environments.

Familiarity with multi-modal data integration and analysis.

Strong problem-solving skills and the ability to thrive in ambiguous, fast-paced settings.

Excellent communication skills for cross-functional teamwork.