1

Generative Ai Engineer Intern Jobs in Rochester, NY

AI Engineer

Rochester, NY · On-site

$50K - $112K/yr

... generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications powered by foundation models - Developing automated evaluation ...

AI Solutions Engineer

Rochester, NY · On-site

$120 - $150/hr

You will partner with clients to identify high-impact Generative AI use cases, evaluate data ... Implement prompt engineering strategies, few-shot learning, and fine-tuning approaches for domain ...

As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate hands-on across high ...

2027 PhD Research Engineering Intern/Co-op

Rochester, NY · On-site

$16.50 - $21.50/hr

As an AMD intern and co-op, you'll be placed at the epicenter of the AI ecosystem, working ... We are seeking a highly motivated Research Engineering intern/co-op to join our team. In this role-

next page

Showing results 1-20

Generative Ai Engineer Intern information

See Rochester, NY salary details

$10

$19

$29

How much do generative ai engineer intern jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for generative ai engineer intern in Rochester, NY is $19.06, according to ZipRecruiter salary data. Most workers in this role earn between $15.91 and $20.62 per hour, depending on experience, location, and employer.

What does a generative AI engineer intern do?

A Generative AI Engineer Intern assists in developing and testing machine learning models, specifically those that can create new content such as text, images, or audio. They work with frameworks like TensorFlow or PyTorch, collaborate with senior engineers, and help improve the performance and reliability of generative AI systems. Interns may also be involved in data preprocessing, model evaluation, and keeping up with the latest research in artificial intelligence.

What skills and qualifications are needed to thrive as a generative AI engineer intern?

To thrive as a Generative AI Engineer Intern, you need a solid understanding of machine learning fundamentals, programming skills (especially in Python), and coursework or experience in artificial intelligence or computer science. Familiarity with deep learning frameworks like TensorFlow or PyTorch and version control systems such as Git is typically required, and relevant coursework or certifications in AI/ML are advantageous. Strong problem-solving skills, curiosity, and the ability to communicate complex ideas clearly help interns stand out. These skills and qualities are crucial for quickly learning advanced AI techniques, contributing to team projects, and driving innovation in a rapidly evolving field.

What types of projects can a generative AI engineer intern expect to work on during their internship?

As a Generative AI Engineer Intern, you can expect to work on projects involving the development, training, and evaluation of generative models such as GANs, VAEs, or transformer-based architectures. Typical tasks may include data preprocessing, model implementation, fine-tuning, and running experiments to improve model performance. Interns often collaborate closely with data scientists, software engineers, and research teams, gaining exposure to both research and application of AI in real-world products. This role provides hands-on experience with state-of-the-art tools and frameworks, offering a valuable foundation for a future career in AI engineering or research.

What is the difference between Generative Ai Engineer Intern vs Machine Learning Engineer Intern?

AspectGenerative Ai Engineer InternMachine Learning Engineer Intern
Required CredentialsBasic knowledge of AI, programming, and some coursework in machine learning or AIStrong foundation in machine learning, programming, and data analysis, often with coursework or certifications
Work EnvironmentTech companies, startups, research labs focusing on AI applicationsTech firms, research institutions, and companies applying machine learning models
Industry UsageDeveloping generative models like GPT, DALL·E, and similar AI toolsBuilding predictive models, data pipelines, and machine learning algorithms

While both roles involve AI and machine learning, a Generative Ai Engineer Intern focuses specifically on creating generative models like text, images, or audio, whereas a Machine Learning Engineer Intern works broadly on developing and deploying various machine learning algorithms across different applications.

What are the most commonly searched types of Generative Ai Engineer jobs in Rochester, NY?

The most popular types of Generative Ai Engineer jobs in Rochester, NY are:

What cities near Rochester, NY are hiring for Generative Ai Engineer Intern jobs?

Cities near Rochester, NY with the most Generative Ai Engineer Intern job openings:

Infographic showing various Generative Ai Engineer Intern job openings in Rochester, NY as of August 2026, with employment types broken down into 11% Internship, 72% Full Time, and 17% Part Time. Highlights an 100% In-person job distribution, with an average salary of $39,639 per year, or $19.1 per hour.

Cloud Engineer- Data/AI Focused

Innovative Solutions

Rochester, NY • On-site

$113K - $135K/yr

Full-time

Re-posted 19 days ago


Job description

As a Data & AI Engineer, you’ll build and deploy modern data pipelines and generative AI solutions on AWS — from scalable ETL/ELT workflows and cloud data platforms to production-grade RAG systems and AI agents. One engagement you may be designing and optimizing data pipelines using Glue, Lambda, and Redshift, the next you’re building GenAI applications powered by Bedrock, Claude, and vector databases to enable intelligent search and automation. You’ll work directly with clients to deliver end-to-end data and AI solutions that are secure, scalable, and production-ready.


What You’ll Do:

  • Implementing data pipelines using AWS services such as Glue, Lambda, Step Functions, and EMR
  • Creating and maintaining data extraction, transformation, and loading processes
  • Configuring and optimizing AWS database services including RDS, Aurora, Redshift, and DynamoDB
  • Implementing data lakes using S3 and related AWS services
  • Designing and building production-ready Generative AI applications using Amazon Bedrock and foundation models such as Anthropic Claude
  • Building and optimizing RAG (Retrieval-Augmented Generation) pipelines with vector databases
  • Developing AI agents and multi-agent orchestration systems using frameworks like LangChain or LlamaIndex
  • Writing and testing SQL queries and stored procedures
  • Documenting technical solutions and providing knowledge transfer to customers
  • Supporting the implementation of data governance and security controls
  • Troubleshooting and resolving issues with data pipelines and AI services
  • Participating in code reviews and implementing feedback
  • Assisting with proof-of-concept implementations for customer engagements

Required Skills:

  • 5+ years of software engineering experience with at least 2+ years focused on AI/ML, data engineering, or cloud-native development
  • 2+ years of hands-on AWS experience with production deployments
  • 1+ years of direct Generative AI experience (LLMs, embeddings, RAG, agents)
  • Proven track record delivering production AI applications from concept to deployment
  • Strong understanding of software engineering best practices (version control, testing, code review, documentation)
  • Experience working in agile/scrum environments with distributed teams
  • Excellent problem-solving skills and ability to work independently with minimal supervision
  • Strong written and verbal communication skills for client-facing interactions

Preferred:

  • Technical familiarity with AWS data and AI/ML services and modern data engineering practices
  • Hands-on experience with ETL/ELT processes and data transformation
  • Exposure to Generative AI concepts including LLMs, embeddings, RAG, and agent frameworks
  • Ability to write and optimize SQL queries across various database platforms
  • Knowledge of data modeling concepts and best practices
  • Strong analytical and problem-solving skills
  • Eagerness to learn new technologies and keep up with cloud and AI innovations
  • Excellent communication skills with the ability to explain technical concepts clearly
  • Attention to detail and commitment to solution quality
  • Collaborative mindset with strong teamwork capabilities
  • Experience or interest in automation and infrastructure as code
The salary range provided is a general guideline. When extending an offer, Innovative considers factors including, but not limited to, the responsibilities of the specific role, market conditions, geographic location, as well as the candidate’s professional experience, key skills, and education/training.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.