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Internship Machine Learning Engineer New Grad Jobs in California

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy ... About the role: We're looking for an early career Machine Learning Engineer to join our team. In ...

Tapestry

Machine Learning Engineer

Mountain View, CA

K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy ... About the role: We're looking for an early career Machine Learning Engineer to join our team. In ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

... Machine Learning Engineer with experience developing ML models for computer vision and graphics ... We perform applied research development to adapt state-of-the-art methods or implement new methods ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

... Machine Learning Engineer with experience developing ML models for computer vision and graphics ... You will perform applied research development to adapt state-of-the-art methods or implement new ...

Intel

Machine Learning Engineer

Santa Clara, CA · On-site

Ability to learn new technologies fast and adapt to changes with open-mindedness. Requirements ... internship experiences and or schoolwork/classes/research. Benefits at Intel Our total rewards ...

Intel

Machine Learning Engineer

Folsom, CA

Ability to learn new technologies fast and adapt to changes with open-mindedness. Requirements ... internship experiences and or schoolwork/classes/research. Benefits at Intel Our total rewards ...

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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:
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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

Maxinsights Corporation

Santa Clara, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago

Job description

Job Description:Machine Learning Engineer

The Role

We are looking for a Machine Learning Engineer to join our core team building scalable ML systems for real-world perception and embodied intelligence.

In this role, you will work on end-to-end machine learning systems, spanning data collection, model training, evaluation, and deployment. You will collaborate closely with researchers,

engineers, and product teams to turn complex real-world data into robust, production-ready ML solutions.

This role is well-suited for engineers who enjoy working across the ML stack, are comfortable operating in ambiguous problem spaces, and are excited about applying modern deep learning methods to real-world perception, human-centric, and embodied AI problems.

Responsibilities

• Design, build, and own end-to-end machine learning systems, from data exploration and model development to evaluation and deployment on large-scale, real-world data.

• Apply state-of-the-art ML techniques to new problem domains and optimize models and pipelines for performance, efficiency, and reliability in production environments.

• Drive measurable improvements in model performance, system robustness, and product capabilities through applied machine learning.

• Collaborate closely with cross-functional teams to translate research ideas and product requirements into scalable ML solutions.

• Contribute to technical design, code quality, and best practices, and help shape the long- term direction of the company’s machine learning platform.

 

Minimum Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.

• 3+ years of experience building and shipping machine learning systems.

• Strong proficiency in Python and experience with at least one major deep learning framework (e.g., PyTorch, TensorFlow).

• Solid understanding of modern deep learning concepts, training workflows, model

evaluation, and experience working with real-world, production-oriented ML pipelines.

• Strong problem-solving skills and ability to work effectively in a fast-moving, collaborative environment.

 

Preferred Qualifications

• PhD in a relevant field with a research focus in robot learning, embodied AI, or visual perception.

• Experience with end-to-end ML systems, including data collection, training, inference, and deployment.

• Background in computer vision, perception, or multi-modal machine learning, including egocentric or human-centric perception.

• Familiarity with large-scale training, experimentation infrastructure, or production ML systems.

• Ability and interest in learning new problem domains, data modalities, and ML techniques quickly.

• Publications in leading venues, open-source contributions, or demonstrated impact in applied ML or AI systems.

What We Offer

• Opportunity to work on challenging, high-impact projects the define the future of robotics and embodied AI.

• A collaborative, innovative, and fast-paced work environment.

• Competitive salary and options package.

• A clear path for career growth in technical leadership.

• Direct collaboration with leading experts in the field of robotics and AI.

Default Benefits:

  • Health insurance

  • Vision care

  • Dental coverage:

  • 401(k)

  • Paid holidays

  • PTO (Paid Time Off)

  • Sick leave