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Startup Machine Learning Intern Jobs (NOW HIRING)

GPTZero

Machine Learning Intern

New York, NY · On-site

Past intern projects have been the focus of demos to VCs and state-level policy leaders ... startup environment * understanding of how machine learning models fail in the wild Who you'll be ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

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Startup Machine Learning Intern information

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$25.5K

$42.6K

$88K

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

As of Jun 11, 2026, the average yearly pay for startup machine learning intern in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are the typical responsibilities of a Startup Machine Learning Intern, and how do they contribute to the team's goals?

As a Startup Machine Learning Intern, you can expect to work on a mix of data preparation, model development, and experimental analysis. Interns often collaborate closely with data scientists, engineers, and product managers to prototype and test machine learning solutions that address real business problems. You'll likely take ownership of individual tasks, such as cleaning datasets, building and validating models, and reporting results to the team. This hands-on environment offers exposure to the full machine learning pipeline and provides opportunities to make meaningful contributions to the company's progress.

What does a Startup Machine Learning Intern do?

A Startup Machine Learning Intern typically assists in developing, testing, and deploying machine learning models to solve real-world business problems in a fast-paced startup environment. Their responsibilities may include data preprocessing, feature engineering, model selection, and performance evaluation. Interns often collaborate closely with data scientists and software engineers, gaining hands-on experience with tools like Python, TensorFlow, or PyTorch. The role provides an opportunity to contribute directly to innovative projects and learn about the startup culture.

What are the key skills and qualifications needed to thrive as a Startup Machine Learning Intern, and why are they important?

To thrive as a Startup Machine Learning Intern, you typically need a solid understanding of machine learning concepts, programming proficiency in Python, and coursework or experience in data science or statistics. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and data visualization libraries, as well as version control systems like Git, is highly valued. Strong problem-solving skills, initiative, and the ability to communicate complex ideas clearly are essential soft skills in a dynamic startup environment. These competencies enable interns to quickly contribute to projects, adapt to evolving tasks, and support innovation within fast-paced teams.

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

AspectStartup Machine Learning InternStartup Data Scientist
Required CredentialsTypically pursuing or recent graduate in CS, Data Science, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields; often with experience
Work EnvironmentEntry-level, learning-focused, collaborative team settingAdvanced projects, strategic decision-making, leadership roles
Employer & Industry UsageStartups, tech companies, research labsStartups, tech firms, larger organizations with data teams

The Startup Machine Learning Intern role is an entry-level position aimed at gaining practical experience in machine learning within startup environments. In contrast, a Startup Data Scientist typically has more experience and handles complex data analysis, model development, and strategic insights. The internship is ideal for students or recent grads, while data scientists are more senior roles focused on driving data-driven decisions.

More about Startup Machine Learning Intern jobs
What cities are hiring for Startup Machine Learning Intern jobs? Cities with the most Startup Machine Learning Intern job openings:
What are the most commonly searched types of Startup Machine Learning jobs? The most popular types of Startup Machine Learning jobs are:
What states have the most Startup Machine Learning Intern jobs? States with the most job openings for Startup Machine Learning Intern jobs include:
What job categories do people searching Startup Machine Learning Intern jobs look for? The top searched job categories for Startup Machine Learning Intern jobs are:
Startup Machine Learning Intern jobs near you
Infographic showing various Startup Machine Learning Intern job openings in the United States as of June 2026, with employment types broken down into 78% Full Time, 11% Part Time, and 11% Nights. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Applied Machine Learning Intern

WaveWorks Technologies Inc

Seattle, WA

Full-time

Posted 15 days ago

Job description

Applied Machine Learning Intern

WaveWorks is building applied AI systems for real-world industrial environments. We are seeking a hands-on Applied Machine Learning Intern to work directly on live deployment data, develop modeling approaches, and take ownership of analysis for an active site.


RESPONSIBILITIES

  • Process, clean, and structure large-scale audio/time-series datasets
  • Align data with ground truth and validate data quality
  • Develop and evaluate modeling approaches for predictive maintenance
  • Design and run structured experiments, analyze results, and document findings
  • Improve data workflows and evaluation pipelines


REQUIRED QUALIFICATIONS

  • Pursuing a degree in Computer Science, Electrical Engineering, Data Science, or related field
  • Strong Python skills
  • Experience with ML frameworks (PyTorch, TensorFlow, or scikit-learn)
  • Comfortable working with real-world, noisy datasets
  • Strong analytical and documentation skills


PREFERRED QUALIFICATIONS

  • MS or PhD candidate in a relevant technical field
  • Experience with audio processing or time-series feature engineering
  • Familiarity with anomaly detection
  • Exposure to signal processing concepts (FFT, spectrograms, filtering)
  • Experience designing and evaluating structured ML experiments
  • Self-driven and comfortable operating in an early-stage environment



WaveWorks is committed to a friendly and welcoming working environment. WaveWorks does not discriminate based on race, gender, age, religious affiliation, or any other legally protected status.

WaveWorks is located in downtown Seattle, Washington.



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