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Machine Learning Developer Intern Jobs in Burlington, VT

Unilever

Ice Cream Packaging Engineer

South Burlington, VT · On-site

$71K - $107K/yr

We embrace digital, use data to make better decisions, and keep learning, including how AI can help ... and machinery Preferably, experience with ArtiosCAD Leadership: Motivated, self-starter and ...

Flow Control Group

Service Technician

Burlington, VT · On-site

$27 - $34/hr

Troubleshoot and evaluate electrical diagrams and machine faults. * Provide technical service ... FCG University learning and training platform available to all employees offering over 80k courses.

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All JobsMachine Learning Developer Intern JobsMachine Learning Developer Intern Jobs in Burlington, VT

Machine Learning Developer Intern information

See Burlington, VT salary details

$25.6K

$42.8K

$88.3K

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

As of Jun 9, 2026, the average yearly pay for machine learning developer intern in Burlington, VT is $42,750.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,600.00 and $46,200.00 per year, depending on experience, location, and employer.

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 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, and why are they important?

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.

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.

Machine Learning Developer Intern jobs near you
Post Doctoral Associate

Post Doctoral Associate

University of Vermont

Burlington, VT

Other

Posted 14 days ago

University Of Vermont rating

8.2

Company rating: 8.2 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

110th of 535 rated colleges and universities

Job description

Position Details
Advertising/Posting Title Post Doctoral Associate in Civil and Environmental Engineering at UVM Posting Summary
Join a vibrant research community at the University of Vermont as a Postdoctoral Scholar. UVM is an R1 research university guided by Our Common Ground values that prioritizes transdisciplinary research and collaboration as a strategy for continued strengthening of scientific inquiry and education. Burlington is a vibrant community located on the shores of Lake Champlain, between the Adirondack and Green Mountains. With year-round recreational opportunities, safe neighborhoods and excellent schools, this progressive community has been frequently cited as being one of the healthiest and best cities in the US in which to live.
The Postdoctoral Scholar will play a key role in advancing NSF AQUA-CLIME convergence research under the supervision and mentorship of Dr. Raju Badireddy in the Department of Civil and Environmental Engineering. The position involves laboratory- and field-oriented research focused on developing and deploying novel low-cost microsensors to investigate how climate-driven disturbances- including flooding, droughts, and wildfires- affect the water quality across diverse hydroclimatic conditions, ranging from humid to arid regions. The project align with our institution's vision to pursue world-class research develop leaders in science and engineering, fostering transdisciplinary collaboration and impactful discoveries.
Research Objectives: The project tests two central hypotheses: (1) that flood, droughts, and wildfires generate substantially different nutrient and emerging contaminant sources, sinks, and transport pathways compared to similar events in other seasons; and (2) that increasingly frequent floods alter watershed function in ways that reduce nutrient retention and other contaminants. Research will build on previous work on developing low-cost nutrient electrochemical microsensors and will leverage two to three heavily instrumented Vermont watersheds spanning a range of land uses, with particular emphasis on how export pathways and processes vary seasonally.
Responsibilities: A central component of this work involves both laboratory and field validation of novel microsensors, which will be deployed alongside standard in-stream sensors and transitional grab-sampling methods. The Scholar will develop proficiency in operating a broad range of high-frequency sensing platforms and in analyzing large environmental datasets to generate insights into watershed functioning under changing climate scenarios.
Qualifications: The candidates must have a Ph.D. in Environmental Engineering or related field by the start date and demonstrate expertise in fabricating and testing microsensors for environmental contaminants in water and soil systems. Specifically, the position seeks candidates with a strong background in environmental engineering, electrochemistry, material science, environmental nanotechnology, and electronics focusing on in-situ chemical and physical sensing technologies, as is proficiency in advanced statistical analysis- particularly in R or similar- for interpreting large environmental datasets. Ideal candidates will have a robust publication record, experience with interdisciplinary projects, and a proven ability to foster inter-institutional collaborations. Additionally, they will have experience guiding undergraduate and graduate students on transformative research and high-impact journal publications, with a commitment to education, outreach, and collaborations. The candidate will have ability to effectively communicate complex concepts to diverse stakeholders.
Research Community: The successful candidate will join our cutting-edge, transdisciplinary research community (35 plus members from Vermont, South Dakota, and New Mexico) working across sensor development and distributed sensor networks, climate modeling, and Artificial Intelligence/Machine Learning. The position also offers meaningful engagement with academic, industry, farming communities and Native Americans Communities across three jurisdictions: Vermont, South Dakota, and New Mexico.
Appointment: This is a one-year position with the possibility of a one-year extension contingent on satisfactory progress. The annual salary is competitive and commensurate with federal agency guidelines, accompanied by an excellent benefits (https://www.uvm.edu/hrs/postdoctoral-associates-fellows-overview). The position provides opportunities for professional development, including media and communications training. The expected start date is August 1, 2026.
Minimum Qualifications (or equivalent combination of education and experience)
The candidates must have a Ph.D. in Environmental Engineering or related field by the start date and demonstrate expertise in fabricating and testing microsensors for environmental contaminants in water and soil systems. Specifically, the position seeks candidates with a strong background in environmental engineering, electrochemistry, material science, environmental nanotechnology, and electronics focusing on in-situ chemical and physical sensing technologies, as is proficiency in advanced statistical analysis- particularly in R or similar- for interpreting large environmental datasets. Ideal candidates will have a robust publication record, experience with interdisciplinary projects, and a proven ability to foster inter-institutional collaborations. Additionally, they will have experience guiding undergraduate and graduate students on transformative research and high-impact journal publications, with a commitment to education, outreach, and collaborations. The candidate will have ability to effectively communicate complex concepts to diverse stakeholders.
Desirable Qualifications Anticipated Pay Range $63,480 - $77,076 Other Information
Support departmental initiatives, assist with occasional teaching or guest lecturing, serve on committees, or attend training sessions as appropriate.
Special Conditions Contingent on continued funding, Background Check required for this position FLSA Exempt Union Position No
Posting Details

Position will be posted for a minimum of one week, after which it is subject to removal without notice.

Job Location Burlington, Vermont, United States Job Open Date 04/24/2026 Job Close Date (Jobs close at 11:59 PM EST.) Open Until Filled No
Our Common Ground Statement

The University of Vermont is a welcoming, educationally purposeful community committed to creating an inclusive environment that embraces intellectual diversity and global perspectives. We seek to prepare students to be accountable leaders who will bring to their work a grasp of complexity, effective problem-solving and communication skills, and an enduring commitment to learning and ethical conduct. Members of the University of Vermont community embrace and advance the values of Our Common Ground: Respect, Integrity, Innovation, Openness, Justice, and Responsibility. Staff play a critical role in this effort and the successful candidate will demonstrate a strong commitment to UVM's mission and advancing Our Common Ground values through the execution of their job duties.

Position Information
Position Title Post Doctoral Associate Posting Number S6063PO Department Civil & Env Engineering/54030 Position Number 00027858 Percent of Full-Time 1.0 Standard Hours at 1.0 FTE 37.5 Term (months per year) 12

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