Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Work closely with internal teams including Data Science, Data Engineering, Paylocity’s Cloud Center of Excellence (CCOE), DevOps, and Delivery Platforms to comprehend requirements and ensure that machine learning engineering solutions are aligned with overarching business goals and priorities.

• Utilize advanced big data technologies on AWS with Databricks and Spark to create scalable and efficient machine learning solutions for millions of users.

• Develop automated data and modeling pipelines, collaborating with internal teams to facilitate smooth integration and deployment of machine learning software features.

• Lead the enhancement of CI/CD workflows, ensuring scalability and resilience while tackling complex automation challenges alongside DevOps and Delivery Platforms.

• Proactively identify and resolve issues and bugs, ensuring that AppSec vulnerabilities are detected and rectified, in close collaboration with Application Security and CCOE teams.

• Promote the adoption of best practices in machine learning engineering throughout teams, contributing to the creation of formal training programs and materials for MLE tool adoption.

• Engage actively in cross-functional meetings and discussions, providing feedback, insights, requirements, and inquiries to ensure alignment and foster project success.

⛳️ Requirements

• Bachelor’s degree with a minimum of 3 years of successful machine learning engineering experience or a similar role at software companies; alternatively, an advanced degree (master’s or PhD) in machine learning engineering, data engineering, computer science, engineering, statistics, mathematics, data science, or another quantitative field is preferred, with no additional experience necessary.

• Proven experience in constructing production-grade machine learning models and infrastructure using Python.

• Strong foundation in advanced Python and big data technologies.

• Familiarity with cloud infrastructure (e.g., AWS, GCP, or Azure).

• Demonstrated experience with Infrastructure as Code (IAC) tools (e.g., CDK, Pulumi, etc.).

• Proven ability to leverage machine learning engineering to achieve business outcomes.

• Competent in translating business challenges into machine learning engineering tasks and effectively communicating results to non-technical audiences.

• Capable of thriving in a collaborative environment with a willingness to share ideas.

• Able to work autonomously and deliver high-quality results while being open to seeking input from team members.

• Solid understanding of data engineering and software engineering principles.

• Self-driven, adaptable, and highly detail-oriented.

🏝️ Benefits

• Medical

• Dental

• Vision

• Life insurance

• Disability insurance

• 401(k) matching

• Perks designed to support you, your family, and your finances

• Career development opportunities