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Internship Machine Learning Engineer New Grad Jobs in California

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 ...

Pattern AI

Machine Learning Engineer

San Mateo, CA

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're building a new type of firm, where live capital is the training ground for an intelligence ... We're looking for an exceptional Machine Learning Engineer to help build the systems that make this ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

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 ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

We have hybrid offices in London, New York, and Singapore; this role is hybrid based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking a Machine Learning Engineer to contribute to the development of tools and ... new machine learning workflows and pipelines into our product and deploy to customers. • Ensure ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

We have hybrid offices in London, New York, and Singapore; this role is hybrid based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

Adobe, Inc.

Machine Learning Engineer

San Jose, CA · On-site

The Opportunity Adobe is looking for a Machine Learning Engineer who will apply AI and machine ... Collaborate with product management and engineering groups to develop new products and features.

Adobe

Machine Learning Engineer

San Jose, CA · On-site

The Opportunity Adobe is looking for a Machine Learning Engineer who will apply AI and machine ... Collaborate with product management and engineering groups to develop new products and features.

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

The Senior Machine Learning Engineer will be responsible for designing, building, and scaling advanced software systems to automate Design for Manufacturing analysis, utilizing deep learning models ...

Atoms

Machine Learning Engineer

Mountain View, CA · On-site

As a Machine Learning Engineer at Atoms, you'll be an integral part of building out the state-of-the-art AI intelligence engine and applications for the food industry. Responsibilities : • Leverage ...

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All JobsInternship Machine Learning Engineer New Grad JobsInternship Machine Learning Engineer New Grad Jobs in California

Internship Machine Learning Engineer New Grad information

What types of projects do Machine Learning Engineer interns typically work on, and how do these contribute to the overall team's goals?

Machine Learning Engineer interns often work on hands-on projects such as data preprocessing, model development, and conducting experiments to validate algorithms under the guidance of senior engineers. These projects might include building prototypes, optimizing existing machine learning models, or supporting data collection and annotation efforts. Interns are expected to collaborate closely with data scientists, software engineers, and product teams to align their work with real business needs. This experience not only helps interns build technical skills but also provides insight into how machine learning solutions are integrated into larger products or services.

What does an Internship Machine Learning Engineer New Grad do?

An Internship Machine Learning Engineer New Grad typically works on developing, testing, and optimizing machine learning models under the guidance of senior engineers or data scientists. Their responsibilities often include data preprocessing, feature engineering, model training, and evaluating model performance. They may also collaborate with cross-functional teams to integrate models into production or contribute to research projects. This role provides hands-on experience with real-world data and the opportunity to learn industry-standard tools and practices.

What are the key skills and qualifications needed to thrive as an Internship Machine Learning Engineer New Grad, and why are they important?

To thrive as an Internship Machine Learning Engineer New Grad, you need a strong grasp of programming (especially Python), machine learning algorithms, data structures, and a relevant degree or coursework in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Strong analytical thinking, problem-solving abilities, and a willingness to learn make you stand out in this position. These skills enable you to contribute effectively to projects, quickly adapt to new challenges, and support innovative solutions in a fast-evolving field.

What is the difference between Internship Machine Learning Engineer New Grad vs Machine Learning Engineer?

AspectInternship Machine Learning Engineer New GradMachine Learning Engineer
Required CredentialsTypically pursuing or recently completed a Bachelor's or Master's in CS, Data Science, or related fieldsBachelor's or higher in CS, Data Science, or related fields; often requires some professional experience
Work EnvironmentTemporary, learning-focused internship, often part-time or summerFull-time professional role in a team, responsible for deploying ML models and projects
Employer & Industry UsageInternships offered by tech companies, startups, and research labs; industry-wideFull-time roles in tech, finance, healthcare, and other sectors utilizing ML

The main difference between an Internship Machine Learning Engineer New Grad and a Machine Learning Engineer is experience level and job responsibilities. Internships are temporary, learning-focused positions for recent graduates or students, while full-time Machine Learning Engineers handle ongoing projects, deployment, and optimization of ML models in a professional setting.

What are the most commonly searched types of Machine Learning Engineer New Grad jobs in California? The most popular types of Machine Learning Engineer New Grad jobs in California are:
What are popular job titles related to Internship Machine Learning Engineer New Grad jobs in California? For Internship Machine Learning Engineer New Grad jobs in California, the most frequently searched job titles are:
What job categories do people searching Internship Machine Learning Engineer New Grad jobs in California look for? The top searched job categories for Internship Machine Learning Engineer New Grad jobs in California are:
What cities in California are hiring for Internship Machine Learning Engineer New Grad jobs? Cities in California with the most Internship Machine Learning Engineer New Grad job openings:
Internship Machine Learning Engineer New Grad jobs near you

Machine Learning Engineer

Winaxis

Fremont, CA • On-site

Contractor

Posted 13 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.