Senior ML Engineer — Remote, Cloud AI & Production

Praxis, Inc.; United States; Remote; USD 133,000 - 190,000; Full time

Job summary

Paylocity is growing its Machine Learning Engineering organization. As a Senior Machine Learning Engineer in Product & Technology, you will build and deploy ML solutions to help teams deliver products faster and more reliably at scale for our customers.

You will collaborate with data science and data engineering teams, leverage AWS, Databricks, and Spark, and drive the development of scalable ML models and infrastructure while advancing best practices across the organization.

Qualifications

• Bachelor’s degree with 5 years of machine learning engineering experience or an advanced degree in ML/DS.
• Production-grade ML models and infrastructure built in Python.
• Strong Python and big data technologies background.
• Experience with cloud platforms (AWS, GCP, or Azure).
• Infrastructure as Code tools (CDK, Pulumi, etc.).

Responsibilities

• Collaborate with Data Science, Data Engineering, CCOE, DevOps, and Delivery Platforms to align ML solutions with business goals.
• Leverage AWS Databricks and Spark to develop scalable ML solutions for millions of users.
• Create automated data and modeling pipelines and ensure smooth deployment of features.
• Lead CI/CD workflow optimization with DevOps and Delivery Platforms.
• Identify and resolve issues, ensuring AppSec vulnerabilities are addressed with security teams.
• Promote best practices in ML engineering and develop training materials for tool adoption.
• Participate in cross-functional meetings to drive project success.

Skills

Python

Cloud computing

Big data

Infrastructure as Code

Data engineering

Collaboration

Education

Bachelor's degree in ML/CS/Engineering

Advanced degree (MS/PhD) in ML/data/CS

Tools

Databricks

Spark

CDK

Pulumi

Job description

Paylocity is growing its Machine Learning Engineering organization. As a Senior Machine Learning Engineer in Product & Technology, you will build and deploy ML solutions to help teams deliver products faster and more reliably at scale for our customers.

You will collaborate with data science and data engineering teams, leverage AWS, Databricks, and Spark, and drive the development of scalable ML models and infrastructure while advancing best practices across the organization.