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Mlops Jobs in Rochester, NY (NOW HIRING)

... MLOps tooling and CI/CD pipelines for ML - Experience with vector databases and semantic search architectures - Translating complex business problems into AI solution designs - Contributing to ...

Data Solutions Engineer

Rochester, NY · On-site +1

$113K - $135K/yr

Less than 1 year of experience in Familiarity with AI/ML frameworks, DevOps practices, and MLOps processes for integrating AI solutions. * Snowflake SnowPro - Preferred Live the Paychex Values * Act ...

Data Solutions Engineer

Rochester, NY · On-site

$113K - $135K/yr

Less than 1 year of experience in Familiarity with AI/ML frameworks, DevOps practices, and MLOps processes for integrating AI solutions. * Snowflake SnowPro - Preferred Live the Paychex Values * Act ...

Senior Data Engineer - GCP

Rochester, NY · On-site

$145K - $165K/yr

Experience with GenAI , AI/ML frameworks, and MLOps - including data modeling and metadata that gets a client ready for agentic workloads. * Looker / LookML , Power BI , or other BI tooling on top of ...

Showing results 21-26

Mlops information

What is MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.

What are the key skills and qualifications needed to thrive as an MLOps engineer?

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

Is MLOps in demand?

MLOps is a rapidly growing field as organizations increasingly adopt machine learning models in production. Professionals with skills in cloud platforms, automation, and tools like Kubernetes and Docker are highly sought after, reflecting strong industry demand for MLOps expertise.

Is MLOps outdated?

MLOps is an evolving field focused on deploying and managing machine learning models efficiently. It remains highly relevant as organizations increasingly adopt AI solutions, with skills in automation, cloud platforms, and monitoring tools in demand. Staying current with new tools and best practices is essential for MLOps professionals.

What is the average salary in MLOps?

The average salary for MLOps engineers typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning deployment tend to earn higher salaries.

What are the most commonly searched types of Mlops jobs in Rochester, NY?

The most popular types of Mlops jobs in Rochester, NY are:

What are popular job titles related to Mlops jobs in Rochester, NY?

For Mlops jobs in Rochester, NY, the most frequently searched job titles are:

What job categories do people searching Mlops jobs in Rochester, NY look for?

The top searched job categories for Mlops jobs in Rochester, NY are:

What cities near Rochester, NY are hiring for Mlops jobs?

Cities near Rochester, NY with the most Mlops job openings:

Infographic showing various Mlops job openings in Rochester, NY as of September 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 74% Physical, 5% Hybrid, and 21% Remote job distribution.

ERP AI Engineer - Manager

Rochester, NY

Pwc
Finance and Insurance • 10K+ employees

$99K - $232K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 5 days ago


Key responsibilities

  • Lead and mentor teams of data scientists and ML engineers

  • Manage client relationships and translate business challenges into AI-driven strategies

  • Design and implement AI solution architectures


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

Oracle

Management Level

Manager

Job Description & Summary

At PwC, our people in business application consulting specialise in consulting services for a variety of business applications, helping clients optimise operational efficiency. These individuals analyse client needs, implement software solutions, and provide training and support for seamless integration and utilisation of business applications, enabling clients to achieve their strategic objectives.
In Oracle data and analytics at PwC, you will utilise Oracle's suite of tools and technologies to work with data and derive insights from it. You will be responsible for tasks such as data collection, data cleansing, data transformation, data modelling, data visualisation, and data analysis using Oracle tools like Oracle Database, Oracle Analytics Cloud, Oracle Data Integrator, Oracle Data Visualization, and Oracle Machine Learning.
Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Analyse and identify the linkages and interactions between the component parts of an entire system.
Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
Develop skills outside your comfort zone, and encourage others to do the same.
Effectively mentor others.
Use the review of work as an opportunity to deepen the expertise of team members.
Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
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 serve as both a technical leader and a trusted advisor to clients, combining AI/ML knowledge with business acumen to design and deliver AI solutions that drive measurable client outcomes. As a Manager, you will lead teams of data scientists and ML engineers, manage client relationships, and translate complex business challenges into AI-driven strategies and solutions. This role offers the chance to shape AI solution architecture while driving innovation and excellence in client engagements.
Responsibilities
- Lead and mentor teams of data scientists and ML engineers
- Manage client relationships and promote satisfaction with deliverables
- Translate intricate business challenges into AI-driven strategies
- Design and implement AI solution architectures
- Drive innovation and excellence in client engagements
- Analyze data to derive actionable insights and solutions
- Collaborate with stakeholders to align on project objectives
- Uphold exceptional standards of quality and integrity in every task
What You Must Have
- Bachelor's Degree
- At least 7 years of experience in AI/ML engineering, data science, or a related technical role
What Sets You Apart
- Master's Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related field preferred
- Experience with Large Language Models and prompt engineering
- Building scalable, cloud-native microservices and containerized deployments
- Proficiency with MLOps tooling and CI/CD pipelines for ML
- Experience with vector databases and semantic search architectures
- Translating complex business problems into AI solution designs
- Contributing to business development and proposal writing
- Cloud certifications in AI/ML or solutions architecture preferred
- Familiarity with Responsible AI principles and bias mitigation practices

Travel Requirements

Up to 60%

Job Posting End Date

The salary range for this position is: $99,000 - $232,000. 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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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