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Artificial Intelligence Machine Learning Engineer Jobs in Rochester, NY

Pwc

AI Engineer

Rochester, NY · On-site

$50K - $112K/yr

... engineering to build and deploy software and platform systems that create ... Artificial Intelligence and Machine Learning-based solutions at scale. Your work will involve ...

Pwc

AI & GenAI Data Scientist - Manager

Rochester, NY · On-site

$99K - $232K/yr

In this role at PwC, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based ...

Varsity Tutors

Machine Learning Tutor

Rochester, NY · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Pwc

CTIO AI Engineering Manager

Rochester, NY

$73K - $244K/yr

... Artificial Intelligence and Robotics preferred - Designing, training, and deploying machine ... learning models - Developing scalable, cloud-native microservices using Docker and Kubernetes ...

Paychex

Data Solutions Engineer

Rochester, NY · On-site

$113K - $135K/yr

Overview The Data Solutions Engineer will play a key role in integrating, architecting, and optimizing data systems to support data monetization, analytics, machine learning, artificial intelligence ...

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Showing results 21-40

All JobsArtificial Intelligence Machine Learning Engineer JobsArtificial Intelligence Machine Learning Engineer Jobs in Rochester, NY

Artificial Intelligence Machine Learning Engineer information

See Rochester, NY salary details

$31.1K

$127.1K

$190.9K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for artificial intelligence machine learning engineer in Rochester, NY is $127,052.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,100.00 and $152,900.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

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

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Rochester, NY?

For Artificial Intelligence Machine Learning Engineer jobs in Rochester, NY, the most frequently searched job titles are:

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Rochester, NY look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Rochester, NY are:

What cities near Rochester, NY are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Rochester, NY with the most Artificial Intelligence Machine Learning Engineer job openings:

Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Rochester, NY as of August 2026, with employment types broken down into 100% Full Time. Highlights an 82% In-person, and 18% Remote job distribution, with an average salary of $127,052 per year, or $61.1 per hour.

Group Leader for AI/ML Group (Scientist)

University of Rochester

Rochester, NY • On-site

$100K - $140K/yr

Full-time

Re-posted 15 days ago

University Of Rochester rating

8.3

Company rating: 8.3 out of 10

Based on 189 frontline employees who took The Breakroom Quiz

127th of 631 rated colleges and universities

Job description

Description
The Theoretical Division at the University of Rochester's Laboratory for Laser Energetics (LLE) is planning to create an artificial intelligence/machine-learning (AI/ML) Group to significantly expand LLE's effort in applying ML tools to solve a variety of problems relevant to high-energy-density (HED) sciences, operate current laser facilities (OMEGA and OMEGA EP), as well as design and operate future HED facilities that will deliver ~100 of shots a day and will require sophisticated tools for facility operation, engineering, and data acquisition and analysis. LLE seeks an AI/ML expert to lead this group. The ideal candidate for this role should have a strong background in machine learning with focus on physical science and technology, with experience in leading teams and developing solutions that provide measurable outcomes.
Qualifications
Candidates should have a Ph.D. in physics, astrophysics, computational physics, or a related field.
Application Instructions
Candidate should submit
  • a cover letter
  • a curriculum vitae and a list of publications.
  • at least three letters of recommendation
  • a statement of research interests and accomplishments,
  • a vision statement for the AI/ML group's future; and

SALARY RANGE: $100,000 to $140,000
The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates are set within the job's compensation range, and determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations.

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