Machine Learning Engineer Intern

Machine Learning Engineer Intern in Product & Technology

Paylocity is growing its Machine Learning Engineering organization. Our Machine Learning Engineering team develops infrastructure and tooling that enable data-driven decisions and AI/ML experiences at scale for millions of Paylocity users.

As a Machine Learning Engineer Intern in Product & Technology, you will contribute to well-scoped machine learning engineering work with mentorship and guidance from experienced engineers. You will gain hands-on experience building, testing, and improving ML software, data and modeling pipelines, and supporting infrastructure. You will collaborate closely with Machine Learning Engineers, Data Scientists, Data Engineers, DevOps, and other platform teams to learn how reliable ML solutions are designed and delivered in production environments.

This internship is designed as a learning experience: you are not expected to independently own production systems or architecture. Instead, you will work on meaningful scoped projects, ask questions, incorporate feedback, and develop the engineering judgment needed for an early-career Machine Learning Engineer.

In-Office: This role is intended to be based in Rochester, New York. Interns are expected to work on-site in the designated office environment and participate in Paylocity's internship programming, including the P&T internship summit in Schaumburg, Illinois.

Our Team Is:

• Building infrastructure that can power ML and AI features for millions of users.
• Building and deploying AI capabilities that help customers get more value from the Paylocity platform.
• Treating responsible AI and AI ethics as first-class considerations in our engineering processes.
• Working collaboratively across Machine Learning Engineering, Data Science, Data Engineering, DevOps, security, and platform teams.
• Invested in learning and applying modern machine learning engineering tools, technologies, and practices.

Primary Responsibilities:

• Contribute to the design, implementation, testing, and improvement of shared AI platform capabilities and services within a defined project scope.
• Build on top of AI platform components to support new AI-powered product experiences, including agent workflows, model integrations, and reusable platform tooling.
• Contribute to building or improving conversational interfaces and experiences, including request handling, conversation flows, context management, and integration with backend services or agents.
• Help develop and improve AI observability and evaluation capabilities, including tracing, metrics, quality evaluation, debugging, and monitoring of AI or agent behavior.
• Write clean, maintainable, and well-documented Python code following established engineering standards and best practices.
• Collaborate with Data Science and Data Engineering partners to help integrate models and data workflows into reliable software solutions.
• Contribute to automated testing, CI/CD workflows, monitoring, and troubleshooting for assigned ML engineering work.
• Investigate bugs and technical issues with guidance, document findings, and participate in root-cause analysis and problem resolution.
• Participate in code reviews, incorporate feedback, and learn how engineering teams balance quality, reliability, scalability, and delivery.
• Participate actively in agile ceremonies, technical discussions, and cross-functional meetings.
• Document technical decisions, implementation details, and lessons learned from internship projects.

Required Qualifications:

• Currently pursuing a Master's degree in Computer Science, Machine Learning, Data Science, Data Engineering, Software Engineering, Statistics, Mathematics, or a related quantitative or technical field.
• Foundational programming experience in Python through coursework, academic projects, research, hackathons, or other practical work.
• Foundational understanding of software engineering concepts such as data structures, algorithms, testing, version control, and debugging.
• Coursework, academic, research, or project experience with AI/ML systems, including exposure to AI observability or evaluation concepts such as tracing, quality metrics, model or agent evaluation, prompt/response analysis, or related evaluation frameworks.
• Familiarity with Git or another version control system.
• Ability to work effectively in a collaborative, team-oriented environment and to seek guidance when needed.
• Strong curiosity, attention to detail, and willingness to learn unfamiliar tools and technologies.
• Ability to communicate technical ideas clearly in written and verbal discussions.

Preferred Skills:

• Experience leveraging AI-assisted coding agents or developer tools such as Claude Code, Cursor, GitHub Copilot, or similar tools to support software development, debugging, testing, or technical problem solving.
• Academic, research, internship, or personal project experience building machine learning applications in Python.
• Exposure to data engineering or distributed computing concepts, including Spark, Databricks, or similar technologies.
• Familiarity with cloud platforms such as AWS, GCP, or Azure.
• Exposure to APIs, containers, CI/CD, Infrastructure as Code, or other modern software delivery practices.
• Interest in generative AI, recommendation systems, ML platforms, MLOps, or responsible AI.
• Contributions to open-source software or participation in technical clubs, hackathons, competitions, or research projects.

What You Will Learn:

• How machine learning solutions move from experimentation into reliable, maintainable software.
• How ML engineers collaborate with Data Scientists, Data Engineers, DevOps, security, and product partners.
• How automated pipelines, testing, CI/CD, observability, and cloud infrastructure support production ML systems.
• How to review code, receive technical feedback, debug issues, and communicate engineering tradeoffs.
• How to balance model quality with software quality, scalability, reliability, security, and customer impact.
• How responsible AI considerations are incorporated into the design and delivery of AI/ML features.

Growth and Conversion Opportunity:

This internship is intended to help students with 0 years of professional experience build the skills needed for an early-career Machine Learning Engineering role. High-performing interns may be considered for future full-time opportunities, based on performance, business needs, and available headcount.

Equal Opportunity and Accessibility:

Paylocity is committed to the full inclusion of all individuals. We recruit, train, compensate, and promote regardless of race, religion, color, national origin, sex, disability, age, veteran status, and other protected status as required by applicable law. At Paylocity, we believe diversity makes us better.

We embrace and encourage our employees' differences in age, culture, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion or spiritual belief, sexual orientation, socio-economic status, veteran status, and other characteristics that make our employees unique. We actively cultivate these differences through our employee resource groups (ERGs), employee experiences, perspectives, talents, and approaches to drive innovation in the software and services we provide our customers.

We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. To request reasonable accommodation in the job application or interview process, please contact View email address on click.appcast.io. This email address is exclusively designated for such requests, aligning with federal and state disability laws. Please do not send resumes to this email address, as they will be removed.