Staff ML Engineer: AI Platform Architect (Remote)

Paylocity; United States; On-site; USD 146,600 - 209,400; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Life insurance

Disability insurance

401(k) match

Family support

Job summary

Paylocity is hiring a Staff Machine Learning Engineer for a fully remote role within the United States. You will build and deploy ML solutions, develop data pipelines, and collaborate with Data Science, Data Engineering, and DevOps to scale ML across millions of users.

You will leverage Python, AWS, Databricks, and Spark, drive CI/CD improvements, and embed security and best practices into ML tooling. A strong background in ML engineering and cloud infra is required.

Qualifications

• Bachelor’s degree or higher in a quantitative field; 8+ years of ML engineering or 3+ years with an advanced degree.
• Experience building production-grade ML models and infrastructure in Python.
• Strong background in Python and big data technologies.
• Experience with cloud infrastructure (AWS, GCP, or Azure).
• Demonstrated IaC tooling experience (CDK, Pulumi, etc.).
• Ability to translate business problems into ML engineering solutions and communicate results.

Responsibilities

• Collaborate with Data Science, Data Engineering, and DevOps to align ML solutions with business priorities.
• Leverage AWS, Databricks, and Spark to develop scalable ML solutions for millions of users.
• Create automated data and modeling pipelines and drive deployment of ML features.
• Lead CI/CD workflow optimization for scalable, resilient automation.

Skills

Python

AWS

Databricks

Spark

CI/CD

Machine Learning

Data Engineering

IaC (CDK, Pulumi)

Education

Bachelor’s degree

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

Tools

Databricks

Spark

AWS

CDK

Pulumi

Job description

Paylocity is hiring a Staff Machine Learning Engineer for a fully remote role within the United States. You will build and deploy ML solutions, develop data pipelines, and collaborate with Data Science, Data Engineering, and DevOps to scale ML across millions of users.

You will leverage Python, AWS, Databricks, and Spark, drive CI/CD improvements, and embed security and best practices into ML tooling. A strong background in ML engineering and cloud infra is required.