Machine Learning Engineer

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Paylocity

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1997

👥 HR Tech

☁️ SaaS

🤝 B2B

💰 $10M Venture Round - Paylocity on 2008-05

HR Tech • SaaS • B2B

Paylocity is a provider of cloud-based payroll and human capital management software for businesses of all sizes. Its platform includes payroll, HR, time & labor, benefits administration, talent management (recruiting, onboarding, performance, learning), employee experience tools and AI-driven features, and it serves small businesses through enterprises as well as partners such as accountants, brokers, and tech partners.

📋 Description

• 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.

🎯 Requirements

• Bachelor’s degree with at least 3 years 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.

🏖️ Benefits

• medical • dental • vision • life • disability • 401(k) match • perks that support you, your family, and your finances • career development