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Ml Engineer Intern Jobs (NOW HIRING)

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Thermal Engineering R&D Intern

San Jose, CA · On-site

$19.75 - $25.50/hr

We are seeking a motivated engineering intern to support the development of an AI/ML-driven system for thermal monitoring, prediction, and anomaly detection during semi-conductor tests. The intern ...

Haize Labs

Software Engineer Intern

New York, NY · On-site

$100K - $125K/yr

We are looking for Software Engineering Interns to help develop our reliability platform, with a ... Experience with ML in an applied setting. * Can ramp up quickly to understand our research.

Haize Labs

Software Engineer Intern

New York, NY

$100K - $125K/yr

We are looking for Software Engineering Interns to help develop our reliability platform, with a ... Experience with ML in an applied setting. * Can ramp up quickly to understand our research.

GPTZero

Software Engineering Intern

New York, NY · On-site

Collaborate with our ML, design, and business teams to develop new product initiatives * Wear ... engineering team with both Y-combinator and Obama scholarship recipients, a designer with art ...

WEX, Inc.

PhD Intern - AI/ML/NLP Engineer

$35 - $43/hr

About the team: We are a fast-growing AI Engineering team, driving WEX's strategic vision to ... As a PhD Research Intern, you will apply your deep technical expertise to solve complex, real-world ...

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How much do ml engineer intern jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for ml engineer intern in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What is the difference between Ml Engineer Intern vs Data Scientist Intern?

AspectML Engineer InternData Scientist Intern
Required CredentialsTypically pursuing or holding a degree in Computer Science, Data Science, or related fields; knowledge of machine learning frameworksSimilar educational background; strong statistical and analytical skills; familiarity with data analysis tools
Work EnvironmentFocus on developing and deploying machine learning models, coding in Python, TensorFlow, or PyTorchFocus on analyzing data, creating visualizations, and deriving insights from datasets
Employer & Industry UsageCommon in tech companies, AI startups, and research labsWidely used across tech, finance, healthcare, and consulting firms

Both roles are entry-level internships requiring a background in data-related fields. ML Engineer Interns focus on building and deploying machine learning models, while Data Scientist Interns analyze data to generate insights. The roles often overlap but differ mainly in technical focus and daily tasks.

What are the key skills and qualifications needed to thrive as an ML Engineer Intern, and why are they important?

To thrive as an ML Engineer Intern, you need a solid foundation in programming (especially Python), statistics, and machine learning concepts, typically supported by coursework or hands-on projects. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is expected. Strong problem-solving skills, curiosity, and effective communication help interns collaborate and learn quickly in team environments. These skills are important because they enable interns to contribute meaningfully to real ML projects while rapidly acquiring new knowledge and adapting to evolving technologies.

What are ML Engineer Interns?

ML (Machine Learning) Engineer Interns are students or recent graduates who assist in designing, building, and deploying machine learning models under the guidance of experienced professionals. Their responsibilities often include data preprocessing, experimenting with algorithms, evaluating model performance, and collaborating with software engineers and data scientists. ML Engineer Interns gain hands-on experience with programming languages like Python, libraries such as TensorFlow or PyTorch, and tools for data analysis. This role is a valuable opportunity to learn how machine learning solutions are developed and applied in real-world scenarios.

What types of projects and responsibilities can an ML Engineer Intern expect to work on during their internship?

As an ML Engineer Intern, you can expect to work on a variety of projects ranging from data preprocessing and cleaning to building and testing machine learning models under the guidance of senior engineers. Interns often contribute to tasks such as feature engineering, model evaluation, and deploying models into production environments. You may also collaborate with data scientists and software engineers to integrate ML solutions into larger systems or products. This hands-on experience not only helps develop your technical skills but also provides insight into industry-standard workflows and team structures.
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Ml Engineer Intern jobs near you

Systems Research Engineer Intern - GPU Programming (Fall 2026)

Together AI

San Francisco, CA • On-site

$58 - $63/hr

Internship

Posted 15 days ago

Job description

About The Role
As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.
Responsibilities
  • Optimize and fine-tune GPU code to achieve better performance and scalability
  • Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
  • Stay up-to-date with the latest advancements in GPU programming techniques and technologies
Requirements
  • Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.
  • Knowledge of ML/AI applications and models
  • Knowledge of performance profiling and optimization tools for GPU programming
  • Excellent problem-solving and analytical skills
Internship Program Details
Our fall internship program spans over 12 to 16 weeks where you'll have the opportunity to work with industry-leading engineers building a cloud from the ground up and possibly contribute to influential open source projects. Our internship dates are September 14th to December 18th.
About Together AI
Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Mamba, FlexGen, Petals, Mixture of Agents, and RedPajama.
Compensation
We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 to $63. Our hourly rates are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
Equal Opportunity
Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
Please see our privacy policy at https://www.together.ai/privacy

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