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Senior Machine Learning Engineer
412th Test Wing, Edwards Air Force BaseSenior Machine Learning Engineer responsible for developing infrastructure and tooling for ML solutions. Collaborating with internal teams to drive efficiency and best practices in ML engineering.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building production-grade machine learning models and infrastructure using Python, while leveraging big data technologies on AWS. Proficient in collaborating with cross-functional teams to drive business results through effective machine learning engineering practices.
Highest-signal resume keywords
Machine Learning EngineeringPython ProgrammingAWS Cloud InfrastructureInfrastructure as Code (IAC)Data Engineering
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning ModelsBig Data TechnologiesAutomated Data PipelinesCI/CD WorkflowsAppSec VulnerabilitiesData ScienceStatisticsMathematicsSoftware Engineering FundamentalsQuantitative Analysis
Soft Skills
CollaborationCommunicationProblem-SolvingAdaptabilityDetail Oriented
Tools & Technologies
DatabricksSparkCDKPulumiDevOps Tools
Industry Keywords
Cloud Center of Excellence (CCOE)Machine Learning Engineering Best PracticesProduction-Grade InfrastructureBusiness AlignmentCross-Functional Collaboration
Tech Stack
Tools & technologiesAWSAzureCloudGoogle 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 5 years of machine learning engineering 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 no additional experience required.
- 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
- a 401(k) match
- perks that support you, your family, and your finances
- career development opportunities