Role Summary
Seeking an experienced Data Engineer or Machine Learning Engineer with strong Python development expertise and hands-on experience building and maintaining data and ML pipelines. This role supports the development, automation, and optimization of scalable data infrastructure and production machine learning systems within a secure environment.
The ideal candidate has at least 2 years of professional experience in Python development, AI/ML systems, and data engineering, along with experience working in Linux-based environments.
Required Qualifications
Minimum 2 years of strong Python development experience
Experience with AI/ML systems and data pipelines
Experience working with Apache technologies
Experience developing and consuming REST APIs
Bachelors degree in Computer Science, Engineering, or related field
Active Top Secret clearance with the ability to obtain SCI with polygraph
Proven work experience or formal training as a Data Engineer, Machine Learning Engineer, or similar role
Key ResponsibilitiesPython Software Development
Develop, maintain, and enhance software applications using Python
Use Python to read, create, and modify relational and graph databases
Develop REST API services to interface with databases
Utilize Git for version control and source code management
Apply Agile methodologies and participate in the full Software Development Life Cycle (SDLC)
Follow industry standards and best practices for software development
Data Pipeline & Automation Development
Maintain and enhance existing automation software systems
Design and implement ETL pipelines using Apache Airflow
Develop task automation pipelines using Apache Airflow
Build production-grade machine learning pipelines from prototype models using Python and Airflow
Collaborate with data scientists and algorithm developers to implement ML-enabled applications
Linux & Containerization
Use Linux as the primary development environment
Containerize applications using Docker
Support deployment and optimization of containerized services
Data Infrastructure & Architecture
Design and maintain data infrastructure across SQL and NoSQL environments
Develop and manage data models across various data modalities
Utilize ORMs and best practices in database design
Documentation & Compliance
Maintain and extend technical documentation following best practices
Create technical documentation, flow charts, and system specifications
Ensure documentation supports operational, reporting, and security requirements
Preferred Skills
Experience working in secure or classified environments
Experience deploying ML models to production
Familiarity with scalable data architectures and automation frameworks
Role Summary
Seeking an experienced Data Engineer or Machine Learning Engineer with strong Python development expertise and hands-on experience building and maintaining data and ML pipelines. This role supports the development, automation, and optimization of scalable data infrastructure and production machine learning systems within a secure environment.
The ideal candidate has at least 2 years of professional experience in Python development, AI/ML systems, and data engineering, along with experience working in Linux-based environments.
Required Qualifications
Minimum 2 years of strong Python development experience
Experience with AI/ML systems and data pipelines
Experience working with Apache technologies
Experience developing and consuming REST APIs
Bachelors degree in Computer Science, Engineering, or related field
Active Top Secret clearance with the ability to obtain SCI with polygraph
Proven work experience or formal training as a Data Engineer, Machine Learning Engineer, or similar role
Key ResponsibilitiesPython Software Development
Develop, maintain, and enhance software applications using Python
Use Python to read, create, and modify relational and graph databases
Develop REST API services to interface with databases
Utilize Git for version control and source code management
Apply Agile methodologies and participate in the full Software Development Life Cycle (SDLC)
Follow industry standards and best practices for software development
Data Pipeline & Automation Development
Maintain and enhance existing automation software systems
Design and implement ETL pipelines using Apache Airflow
Develop task automation pipelines using Apache Airflow
Build production-grade machine learning pipelines from prototype models using Python and Airflow
Collaborate with data scientists and algorithm developers to implement ML-enabled applications
Linux & Containerization
Use Linux as the primary development environment
Containerize applications using Docker
Support deployment and optimization of containerized services
Data Infrastructure & Architecture
Design and maintain data infrastructure across SQL and NoSQL environments
Develop and manage data models across various data modalities
Utilize ORMs and best practices in database design
Documentation & Compliance
Maintain and extend technical documentation following best practices
Create technical documentation, flow charts, and system specifications
Ensure documentation supports operational, reporting, and security requirements
Preferred Skills
Experience working in secure or classified environments
Experience deploying ML models to production
Familiarity with scalable data architectures and automation frameworks