Machine Learning Engineer

Machine Learning Engineer at Paylocity

Paylocity is an award-winning provider of cloud-based HR and payroll software solutions, offering the most complete platform for the modern workforce. The company has become one of the fastest-growing HCM software providers worldwide by offering an intuitive, easy-to-use product suite that helps businesses automate and streamline HR and payroll processes, attract and retain talent, and build a strong workplace culture.

While traditional HR and payroll providers automate basic HR processes such as payroll and benefits administration, Paylocity goes further by developing tools that HR and businesses need to compete for talent and deliver against the expectations of the modern workforce.

We give our employees what they need to succeed, including great benefits and perks! We offer medical, dental, vision, life, disability, and a 401(k) match, as well as perks that support you, your family, and your finances. And if it’s career development you desire, we provide that, too! At Paylocity, people matter most and have always been at the heart of our business.

Take your career to the next level at one of G2's Top 100 Software Companies. Explore our Product & Technology positions to see where you fit!

This is a fully remote position, allowing you to work from home or location of record within the U.S. with no in-office requirements. You must be available five days per week during designated work hours. The work arrangement for this role is subject to change based on business needs and individual performance. This may include adjustments to on-site requirements or schedule expectations, as necessary.

Position Overview

Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users.

As a Machine Learning Engineer in Product & Technology, you will help Paylocity build and deploy Machine Learning solutions, to help our teams build better products faster, more reliably, and at the scale we see in production for our customers. We develop machine learning models and infrastructure to support internal team strategies and collaborate closely with our data science organization to drive efficiency and best practices. Your primary focus will be to leverage your expertise in software development, machine learning algorithms, and data infrastructure to architect, develop, and optimize machine learning solutions. You will play a key role in driving the development of scalable and efficient machine learning models, contributing to the enhancement of product features, and the overall improvement of our infrastructure.

Our Team Is

• Building infrastructure that can power ML and AI features for millions of users
• Building and deploying platform-wide recommendations to help companies follow HR best practices and allow employees to get the most out of our platform (Paylocity AI page)
• Baking AI Ethics into all our processes as a first-class citizen (Blog Post)
• Working in a collaborative fully remote environment with a desire to share ideas and continuously improve
• Invested in staying current in machine learning engineering by applying the newest tools, technologies, and practices
• Excited to work on cutting-edge technology!

Primary Responsibilities

• Collaborate closely with internal teams such as Data Science, Data Engineering, Paylocity’s Cloud Center of Excellence (CCOE), DevOps, and Delivery Platforms to understand requirements and ensure alignment of machine learning engineering solutions with overall business objectives and priorities.
• Leverage cutting-edge big data technologies on AWS utilizing Databricks and Spark to develop scalable and efficient machine learning solutions for millions of users.
• Create automated data and modeling pipelines, collaborating with internal teams to ensure smooth integration and deployment of machine learning software features.
• Lead the optimization of CI/CD workflows, ensuring scalability and resilience while addressing complex challenges in automation in partnership with DevOps and Delivery Platforms.
• Proactively identify and resolve issues/bugs, ensuring AppSec vulnerabilities are identified and corrected, working closely with Application Security and CCOE teams.
• Drive the adoption of best practices in machine learning engineering across teams, contributing to the development of formal training programs and materials for MLE tool adoption.
• Actively participate in cross-functional meetings and discussions, providing feedback, commentary, requirements, and questions to ensure alignment and drive project success.

Education And Experience

• Bachelor’s degree with at least 3 of machine learning engineering success or similar experience at software companies; or, advanced degree (master’s or PhD) preferred in machine learning engineering, data engineering, computer science, engineering, statistics, mathematics, data science, or other quantitative field, with no additional experience required.
• Experience in building production-grade machine learning models and infrastructure in Python.
• Strong background in advanced Python and big data technologies
• Experience with cloud infrastructure (i.e., AWS, GCP, or Azure).
• Demonstrated experience with Infrastructure as Code (IAC) tools (i.e. CDK, Pulumi, etc.).
• Demonstrated ability to leverage machine learning engineering to drive business results.
• Skilled at translating business problems into machine learning engineering problems and communicating the results to non technical audiences.
• Able to work in a collaborative environment with a desire to share your ideas.
• Able to work independently and complete tasks with high quality, but unafraid to seek out suggestions from other team members.
• Strong understanding of data engineering and software engineering fundamentals.
• Self-motivated, adaptable, and highly detail oriented.

Preferred Skills

• Professional or academic experience in HR, social science or psychology
• Contributions to open-source software in Python
• Enthusiastic about how machine learning and infrastructure can lead to a superior customer experience.
• Be invested in staying current in machine learning and infrastructure by applying new technologies and practices

Physical Requirements

• Ability to sit for extended periods: The role requires sitting at a desk or workstation for long periods, typically 7-8 hours a day.
• Use of computer and phone systems: The employee must be able to operate a computer, use phone systems, and type. This includes using multiple software programs and inquiries simultaneously.

Key skills/competency

• Machine Learning Engineering
• Python Programming
• AWS Cloud Services
• Databricks & Spark
• Data Pipelines
• CI/CD Optimization
• Infrastructure as Code (IaC)
• MLOps Best Practices
• Collaborative Teamwork
• Scalable ML Solutions