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412th Test Wing, Edwards Air Force Base

Staff Machine Learning Engineer

412th Test Wing, Edwards Air Force Base

Staff Machine Learning Engineer role developing and deploying machine learning solutions at Paylocity. Collaborating with internal teams to enhance product features and employee experience.

Posted 7/31/2026full-timeRemote • 🇺🇸 United StatesLead💰 $146,600 - $209,400 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in machine learning engineering, leveraging advanced Python and big data technologies on AWS to develop scalable solutions. Proficient in building production-grade models, optimizing CI/CD workflows, and collaborating across teams to drive business results.

Highest-signal resume keywords
Machine Learning EngineeringAdvanced Python ProgrammingAWS Cloud InfrastructureInfrastructure as Code (IAC)Data Engineering Fundamentals

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Machine Learning ModelsBig Data TechnologiesCI/CD WorkflowsAutomated Data PipelinesApplication SecurityData ScienceStatisticsMathematicsSoftware EngineeringQuantitative Analysis
Soft Skills
CollaborationCommunicationProblem-SolvingAdaptabilityDetail Orientation
Tools & Technologies
DatabricksSparkAWSGCPAzureCDKPulumi
Industry Keywords
Machine Learning EngineeringData EngineeringCloud Center of Excellence (CCOE)DevOpsBusiness Objectives

Tech Stack

Tools & technologies
AWSAzureCloudGoogle Cloud PlatformPythonSpark

About the role

Key responsibilities & impact
  • Collaborate closely with internal teams such as Data Science, Data Engineering, Paylocity’s Cloud Center of Excellence (CCOE), DevOps, and Delivery Platforms to understand requirements and ensure alignment of machine learning engineering solutions with overall business objectives and priorities.
  • Leverage cutting-edge big data technologies on AWS utilizing Databricks and Spark to develop scalable and efficient machine learning solutions for millions of users.
  • Create automated data and modeling pipelines, collaborating with internal teams to ensure smooth integration and deployment of machine learning software features.
  • Lead the optimization of CI/CD workflows, ensuring scalability and resilience while addressing complex challenges in automation in partnership with DevOps and Delivery Platforms.
  • Proactively identify and resolve issues/bugs, ensuring AppSec vulnerabilities are identified and corrected, working closely with Application Security and CCOE teams.
  • Drive the adoption of best practices in machine learning engineering across teams, contributing to the development of formal training programs and materials for MLE tool adoption.
  • Actively participate in cross-functional meetings and discussions, providing feedback, commentary, requirements, and questions to ensure alignment and drive project success.

Requirements

What you’ll need
  • Bachelor’s degree with 8 years of machine learning engineering or similar experience at software companies; or, advanced degree (master’s or PhD) in machine learning engineering, data engineering, computer science, engineering, statistics, mathematics, data science, or other quantitative field, with 3 years of demonstrated machine learning engineering success or similar experience.
  • Experience in building production-grade machine learning models and infrastructure in Python.
  • Strong background in advanced Python and big data technologies
  • Experience with cloud infrastructure (i.e., AWS, GCP, or Azure).
  • Demonstrated experience with Infrastructure as Code (IAC) tools (i.e. CDK, Pulumi, etc.).
  • Demonstrated ability to leverage machine learning engineering to drive business results.
  • Skilled at translating business problems into machine learning engineering problems and communicating the results to non-technical audiences.
  • Able to work in a collaborative environment with a desire to share your ideas.
  • Able to work independently and complete tasks with high quality, but unafraid to seek out suggestions from other team members.
  • Strong understanding of data engineering and software engineering fundamentals.
  • Self-motivated, adaptable, and highly detail oriented.

Benefits

Comp & perks
  • medical
  • dental
  • vision
  • life
  • disability
  • 401(k) match
  • perks that support you, your family, and your finances
  • career development