Manager Machine Learning Engineering

Paylocity

Posted 1mo ago

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Lead Machine Learning Engineering teams in developing and enhancing machine learning infrastructure and solutions
Build and evolve AI platforms that scale across products, domains, and teams
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
Contribute to development of formal training programs and materials for MLE tool adoption
Influence and collaborate with teams across Product & Technology (Data Engineering, Cloud Center of Excellence, Platform teams, Architecture Review Board)
Influence business strategy by leveraging data and metrics and presenting recommendations 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

Bachelor's degree in a quantitative field
5+ years of hands-on AI/ML success at software companies
2+ years of experience managing and leading data teams
Experience writing production grade machine learning infrastructure and/or models in Python
Hands-on experience with cloud infrastructure on AWS (Glue, EMR, Lambda, etc.)
Experience with infrastructure-as-code tooling
Familiar with cloud-based source code management, continuous integration, continuous delivery (GitHub Actions, TeamCity, Octopus, Jenkins, etc.)
Demonstrated ability to lead high-performing teams, inspire others, and drive business results
Skilled at translating business problems into data/ML problems and communicating results to non-technical audiences
Self-motivated, adaptable, and highly detail oriented
Strong sense of curiosity and willingness to learn
Exceptional verbal and written communication skills

Advanced degree (Master's or PhD) in machine learning engineering, computer science, engineering, data science, statistics, mathematics, or another quantitative field
Professional or academic experience in HR, social science or psychology
Invested in staying current in AI/ML by applying new technologies and practices

Skills