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Machine Learning Developer Intern Jobs in Burlingame, CA

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 ...

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 ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site

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 ...

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 models, with a strong understanding of data and model quality Strong programming skills and hands-on experience using one or more deep learning frameworks, such as PyTorch ...

PROPRIUS

Machine Learning Engineer

San Francisco, CA · On-site

Machine Learning Engineer Location: San Francisco, CA Sponsorship: No Relocation: No Industry: Machine Learning Join an artificial intelligence company in San Francisco that excels at visual ...

Qubeaxis

Machine Learning Engineer

San Francisco, CA · On-site

$150 - $200/hr

Job Title Machine Learning Engineer Job ID 20985 Location Work Mode Onsite About the Team Our ML Platform team builds intelligent systems that power recommendations, forecasting, ranking ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$216K - $324K/yr

... machine learning models, with a strong understanding of data and model quality Strong programming skills and hands-on experience using one or more deep learning frameworks, such as PyTorch ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

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Showing results 21-40

All JobsMachine Learning Developer Intern JobsMachine Learning Developer Intern Jobs in Burlingame, CA

Machine Learning Developer Intern information

See Burlingame, CA salary details

$28.8K

$48.1K

$99.4K

How much do machine learning developer intern jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning developer intern in Burlingame, CA is $48,082.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,700.00 and $51,900.00 per year, depending on experience, location, and employer.

What does a machine learning developer intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

What are the key skills and qualifications needed to thrive as a machine learning developer intern?

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

How do machine learning developer interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities near Burlingame, CA are hiring for Machine Learning Developer Intern jobs?

Cities near Burlingame, CA with the most Machine Learning Developer Intern job openings:

Machine Learning Developer Intern jobs near you

Machine Learning Engineer

Fremont, CA • On-site

MM International
See more jobs at MM Internationalexternal

Contractor

Re-posted 8 days ago

Job description

Role: 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 general video screening with PV. Then we send the submission to the client

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

  • CI/CD, Kubernetes, MLflow, TensorFlow, PyTorch, AWS.
  • 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.