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Data Annotation For Ai Jobs in Vermont (NOW HIRING)

AI Engineer

Montpelier, VT · On-site

$50K - $112K/yr

... views for analysis - Building and maintaining data pipelines to support AI model deployment - Applying complex data analysis techniques to discern patterns and trends - Collaborating with team ...

$18 - $50/hr

Potential for full-time offers after university graduation and completion of the program Position Overview: Siemens Digital Industries Software is seeking an AI & Engineering Data Intern to support ...

$18 - $50/hr

Potential for full-time offers after university graduation and completion of the program Position Overview: Siemens Digital Industries Software is seeking an AI & Engineering Data Intern to support ...

$18 - $50/hr

Potential for full-time offers after university graduation and completion of the program Position Overview: Siemens Digital Industries Software is seeking an AI & Engineering Data Intern to support ...

$18 - $50/hr

Potential for full-time offers after university graduation and completion of the program Position Overview: Siemens Digital Industries Software is seeking an AI & Engineering Data Intern to support ...

$18 - $50/hr

Potential for full-time offers after university graduation and completion of the program Position Overview: Siemens Digital Industries Software is seeking an AI & Engineering Data Intern to support ...

$18 - $50/hr

Potential for full-time offers after university graduation and completion of the program Position Overview: Siemens Digital Industries Software is seeking an AI & Engineering Data Intern to support ...

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Data Annotation For Ai information

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What cities in Vermont are hiring for Data Annotation For Ai jobs?

Cities in Vermont with the most Data Annotation For Ai job openings:

Infographic showing various Data Annotation For Ai job openings in Vermont as of September 2026, with employment types broken down into 70% Full Time, 18% Part Time, and 12% Contract. Highlights an 68% In-person, 8% Hybrid, and 24% Remote job distribution.

AI Engineer

Montpelier, VT • On-site

Pwc
Finance and Insurance • 10K+ employees

$50K - $112K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 77 frontline employees who took The Breakroom Quiz


Job description

Industry/Sector

Not Applicable

Specialism

IFS - Information Technology (IT)

Management Level

Associate

Job Description & Summary

The Opportunity
As an AI Engineer, you will be at the forefront of transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Internal Firm Services practice, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based solutions at scale. Your work will involve designing AI systems, data wrangling, and software implementation to enable the AI models to be useful and scalable.
As an Associate, you will focus on learning and contributing to projects while developing your skills and knowledge to deliver quality work. You will engage with different stakeholders to build meaningful connections, learn how to manage and inspire others, and grow your personal brand by deepening your technical knowledge of firm services and technology resources. In increasingly complex situations, you will build acumen to anticipate the needs of your teams and internal stakeholders, embrace ambiguity, ask questions, and use these challenges as opportunities for growth.
In this role, you will take ownership and consistently deliver quality work that drives value for our clients and success as a team. You will be part of a dynamic environment where every experience is an opportunity to learn and grow, opening doors to more opportunities within the firm.
Responsibilities
- Designing and implementing AI systems to transform raw data into actionable insights
- Developing scalable machine learning models using Python and TensorFlow
- Integrating data from various sources to create unified views for analysis
- Building and maintaining data pipelines to support AI model deployment
- Applying complex data analysis techniques to discern patterns and trends
- Collaborating with team members to enhance AI solutions and drive business growth
- Utilizing natural language processing tools like NLTK for text analytics and sentiment analysis
- Implementing neural networks and deep learning methods for advanced AI applications
- Managing data quality and infrastructure to support reliable AI operations
- Engaging in continuous learning to adapt to new technologies and methodologies in AI engineering
What You Must Have
- At least a Bachelor's degree or, in lieu of a degree, demonstrating in addition to the minimum years of experience required for the role, three years of specialized training and/or progressively responsible work experience in Engineering with AI and Machine Learning for each missing year of college is required
- At least 1 years of experience
What Sets You Apart
- In at least one of the following fields of study: Computer and Information Science, Computer Engineering, Computer Management, Management Information Systems, Information Technology
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials

- Building and orchestrating AI agent workflows using frameworks such as LangGraph to automate multi-step reasoning, integrate tools and APIs, and deliver scalable, context-aware solutions
- Applying generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications powered by foundation models
- Developing automated evaluation frameworks, including LLM-as-judge pipelines, regression testing, and adversarial benchmarking, to assess reasoning, tool-calling reliability, and output groundedness
- Optimizing open-weight language models, including LLaMA, Mistral, and Gemma, for local and cloud deployment using quantization, inference acceleration, and model-routing techniques
- Designing agent harnesses and implementing context engineering, memory management, retry logic, and structured output validation to support reliable, multi-step AI workflows
- Demonstrating proficiency in Python and TensorFlow for AI projects
- Utilizing machine learning libraries like Scikit-Learn for data analysis
- Engaging in complex data analysis and pattern recognition
- Implementing AI solutions using open-source software
- Applying natural language processing techniques in real-world applications

Travel Requirements

Up to 20%

Job Posting End Date

The salary range for this position is: $50,500 - $112,500. 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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About pwc

Sourced by ZipRecruiter

We know that the future success of our firm is contingent on equitable experiences for our people. From recruitment to partnership, we’re working hard to give every person an equitable opportunity to grow and to thrive as part of our community of solvers. We understand that establishing and maintaining a fair, equitable and welcoming environment for all people requires building a culture of belonging: a shift from awareness to empathy — while demonstrating inclusive leadership that cultivates trust among our people and our clients. PwC is committed to advancing diversity, equity and inclusion (DEI) through an evidence-based strategy designed to achieve well-defined and meaningful aspirational goals. Our aim is to solve problems for the long term, as that is how we build trust and continue to build on our culture of belonging. At the core of this endeavor are stated goals and a series of linked programs enabling targeted interventions at key moments in our employees’ career trajectories.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

London, London, UK