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Machine Learning Engineer Jobs in Burlington, VT

Experience with computer applications in manufacturing, machine vision, artificial intelligence (AI ... learning and engagement among the members of our team. We strongly encourage those with diverse ...

Experience with computer applications in manufacturing, machine vision, artificial intelligence (AI ... learning and engagement among the members of our team. We strongly encourage those with diverse ...

Experience with computer applications in manufacturing, machine vision, artificial intelligence (AI ... learning and engagement among the members of our team. We strongly encourage those with diverse ...

And in using quality PMA parts for the Air Cycle Machine's rotating group on the CRJ & Dash 8 ... Reverse engineer, troubleshoot, and repair of various aircraft components, both electrical and ...

And in using quality PMA parts for the Air Cycle Machine's rotating group on the CRJ & Dash 8 ... Reverse engineer, troubleshoot, and repair of various aircraft components, both electrical and ...

Software Engineer I

Jericho, VT · On-site

$74K - $111K/yr

We are looking for a Software Engineer I who is eager to learn, grow, and contribute to a high ... You will begin learning how to leverage AI tools such as GitHub Copilot, Claude Code, and MCP-based ...

Software Engineer I

Plattsburgh, NY · On-site

$74K - $111K/yr

We are looking for a Software Engineer I who is eager to learn, grow, and contribute to a high ... You will begin learning how to leverage AI tools such as GitHub Copilot, Claude Code, and MCP-based ...

Software Engineer I

Winooski, VT · On-site

$74K - $111K/yr

We are looking for a Software Engineer I who is eager to learn, grow, and contribute to a high ... You will begin learning how to leverage AI tools such as GitHub Copilot, Claude Code, and MCP-based ...

Software Engineer I

Essex Junction, VT · On-site

$74K - $111K/yr

We are looking for a Software Engineer I who is eager to learn, grow, and contribute to a high ... You will begin learning how to leverage AI tools such as GitHub Copilot, Claude Code, and MCP-based ...

Software Engineer I

Keeseville, NY · On-site

$74K - $111K/yr

We are looking for a Software Engineer I who is eager to learn, grow, and contribute to a high ... You will begin learning how to leverage AI tools such as GitHub Copilot, Claude Code, and MCP-based ...

Software Engineer I

Burlington, VT · On-site

$74K - $111K/yr

We are looking for a Software Engineer I who is eager to learn, grow, and contribute to a high ... You will begin learning how to leverage AI tools such as GitHub Copilot, Claude Code, and MCP-based ...

Software Engineer I

South Burlington, VT · On-site

$74K - $111K/yr

We are looking for a Software Engineer I who is eager to learn, grow, and contribute to a high ... You will begin learning how to leverage AI tools such as GitHub Copilot, Claude Code, and MCP-based ...

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Showing results 1-20

Machine Learning Engineer information

See Burlington, VT salary details

$31K

$126.9K

$190.7K

How much do machine learning engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for machine learning engineer in Burlington, VT is $126,902.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $152,800.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Burlington, VT? The most popular types of Machine Learning Engineer jobs in Burlington, VT are:
What are popular job titles related to Machine Learning Engineer jobs in Burlington, VT? For Machine Learning Engineer jobs in Burlington, VT, the most frequently searched job titles are:
Infographic showing various Machine Learning Engineer job openings in Burlington, VT as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $126,902 per year, or $61 per hour.
Post Doctoral Associate in Civil and Environmental Engineering at UVM

Post Doctoral Associate in Civil and Environmental Engineering at UVM

The University of Vermont

Burlington, VT • On-site

Full-time

Posted 22 days ago


University Of Vermont rating

7.9

Company rating: 7.9 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

181st of 555 rated colleges and universities


Job description

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

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