Manager Machine Learning Engineering

Manager Machine Learning Engineering

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.

• Primary Responsibilities
• Education And Experience
• Preferred Skills

The Manager, Machine Learning Engineering (MLE) has a critical role in our Product and Technology organization. This role requires strong technical expertise as well as strong people and project management experience. This leader will be responsible for helping shape the direction of AI/ML initiatives and driving delivery of business outcomes, while actively investing in the growth and development of team members through coaching, mentorship, and career planning.

This position requires commitment to exceptional results, a strong desire for continuous improvement, and the ability to build a collaborative high performing culture within and across teams. A MLE Manager Will Be Expected To Independently lead Machine Learning Engineering teams in the development and enhancement of our machine learning infrastructure and solutions that impact millions of employees every day. Build and evolve AI platforms that scale across products, domains, and teams at Paylocity. Own and drive end-to-end ML tooling and automation, from infrastructure and data pipelines to model deployment, monitoring, and optimization. Collaborate with data science and engineering teams to drive adoption of best practices in MLE while contributing to the development of formal training programs and materials for MLE tool adoption. Influence and collaborate with other teams across Product & Technology (e.g. Data Engineering, Cloud Center of Excellence, Platform teams, Architecture Review Board, etc.) to ensure alignment and integration of ML capabilities. Influence business strategy by leveraging data and metrics and presenting recommendations and insights to Dir+ leadership. Mentor, coach, and develop teams, fostering technical excellence, professional growth, and leadership capabilities. Oversee and manage multiple projects simultaneously, ensuring alignment with company objectives, resource optimization, and timely delivery. Establish best practices for scalable and reproducible machine learning development, deployment, and governance. Continuously assess team outcomes, processes, and quality to drive improvements. Stay at the forefront of AI and ML advancements, ensuring the team continuously evolves by incorporating the latest technologies, methodologies, and best practices.

• Education And Experience
• Preferred Skills