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Internship Machine Learning Engineer Jobs in Vermont

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ... Engineering, Computer Engineering, or a related field • A history of academic excellence or ...

... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ... Engineering, Computer Engineering, or a related field • A history of academic excellence or ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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Internship Machine Learning Engineer information

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

To excel as an Internship Machine Learning Engineer, you typically need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, often supported by coursework or relevant project experience. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is common, along with proficiency in data processing libraries. Curiosity, strong problem-solving abilities, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can contribute meaningfully to projects, adapt to new challenges, and collaborate productively in a rapidly evolving technical environment.

What types of projects and responsibilities can I expect as an Internship Machine Learning Engineer?

As an Internship Machine Learning Engineer, you will typically support the development, testing, and deployment of machine learning models under the guidance of senior engineers. Your responsibilities may include data preprocessing, exploratory data analysis, implementing algorithms, and evaluating model performance. You'll often collaborate closely with data scientists, software engineers, and product managers, gaining exposure to real-world workflows and tools. This hands-on experience is invaluable for building technical skills and understanding how machine learning solutions are integrated into larger products.

What does an Internship Machine Learning Engineer do?

An Internship Machine Learning Engineer works alongside experienced engineers to help develop, test, and deploy machine learning models. Their responsibilities may include cleaning and preparing data, writing code for model training, evaluating model performance, and contributing to research tasks. Interns often learn to use popular frameworks such as TensorFlow or PyTorch and gain hands-on experience with real-world datasets. This role is designed to help students or recent graduates apply their academic knowledge to practical problems while developing industry-relevant skills.

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

AspectInternship Machine Learning EngineerData Scientist Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, data analysis, programming
Work EnvironmentDeveloping ML models, coding, testingData analysis, visualization, reporting
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, consulting

Internship Machine Learning Engineers focus on developing and testing machine learning models, often requiring programming and basic ML knowledge. Data Scientist Interns analyze data, create visualizations, and generate insights. Both roles are common in tech and data-driven industries, but ML Engineer internships emphasize model deployment, while Data Science internships focus on data analysis and reporting.

What are the most commonly searched types of Machine Learning Engineer jobs in Vermont? The most popular types of Machine Learning Engineer jobs in Vermont are:
What cities in Vermont are hiring for Internship Machine Learning Engineer jobs? Cities in Vermont with the most Internship Machine Learning Engineer job openings:
CTIO-AI Engineer-Sr Associate

CTIO-AI Engineer-Sr Associate

Pwc

Montpelier, VT

$55K - $187K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 27 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 73 frontline employees who took The Breakroom Quiz

20th of 57 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Data Science

Management Level

Senior Associate

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.
Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn't clear, you ask questions, and you use these moments as opportunities to grow.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Respond effectively to the diverse perspectives, needs, and feelings of others.
Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
Use critical thinking to break down complex concepts.
Understand the broader objectives of your project or role and how your work fits into the overall strategy.
Develop a deeper understanding of the business context and how it is changing.
Use reflection to develop self awareness, enhance strengths and address development areas.
Interpret data to inform insights and recommendations.
Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
The Opportunity
As part of the Data and Analytics Engineering team you will develop and implement AI solutions that enhance product offerings. As a Senior Associate, you will analyze complex problems, mentor junior team members, and maintain elevated professional standards while building meaningful client relationships.
Responsibilities
- Build and nurture meaningful relationships with clients
- Utilize advanced analytical techniques to drive innovation
- Work with cross-functional teams to achieve project goals
- Uphold the firm's ethical standards and recommended practices
What You Must Have
- Bachelor's Degree in Computer Science, Data Processing/Analytics/Science, Artificial Intelligence and Robotics
- 3 years of professional experience developing AI/ML systems or integrating AI into products
What Sets You Apart
- Master's Degree preferred
- Possessing advanced proficiency in prompt engineering
- Demonstrating experience deploying LLMs into production
- Designing and optimizing RAG pipelines
- Leading technical discovery in fast-paced environments
- Collaborating effectively with cross-functional leaders
- Advocating for responsible AI principles
- Contributing to AI research or open-source communities
- Demonstrating knowledge of orchestration tools such as LangChain, LlamaIndex, and experience with agent-based systems

Travel Requirements

Up to 20%

Job Posting End Date

The salary range for this position is: $55,000 - $151,470. For residents of Washington state the salary range for this position is: $55,000 - $187,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

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