Summary: Quality Analytics Associates (QAA) is accepting resumes for qualified individual(s) to provide the primary data integration, systems engineering, AI/analytics infrastructure, and engineering support. The engineer will develop data pipelines, evidence transformations, system interfaces, technical architecture, and components needed to support analytical-model execution.
Salary: $80,000 – $90,000 (negotiable)
Responsibilities
- Design and implement data pipelines supporting ingestion and integration of various evidence types.
- Develop processes for data processes for statistical and AI/ML analysis.
- Design technical architectures and presentation.
- Develop and maintain data schemas, evidence models, interfaces, APIs, and integration components.
- Implement mechanisms that preserve data provenance and source-to-output/model traceability.
- Engineer analytical data sets and technical environments supporting model development, testing, evaluation, and demonstration.
- Integrate statistical and machine-learning models developed by the Data Scientist/ML Lead.
- Support implementation of model outputs, explainable indicators, uncertainty information, and supporting evidence within interfaces.
- Support engineering, configuration, integration, testing, troubleshooting, and technical documentation.
- Evaluate system and data dependencies, integration constraints, interoperability considerations, and resource requirements.
- Support cybersecurity, data governance, access-control, authorized-use, and technical risk considerations applicable to the environment.
- Develop or support demonstration environments for evaluation.
- Document technical architecture, data flows, interfaces, dependencies, limitations, and maturation requirements.
- Support transition planning.
Required Qualifications
- Bachelor’s degree in computer science, software engineering, data engineering, systems engineering, information systems, computer engineering, or a related technical discipline. OR equivalent years’ experience
- Demonstrated experience designing or implementing data-intensive software, analytics platforms, data pipelines, or integrated information systems.
- Experience with Python and SQL and with modern data-processing or application-development technologies.
- Experience integrating structured and/or unstructured data from multiple systems or sources.Experience with data transformation, schema design, APIs, databases, and data pipelines.
- Working knowledge of AI/ML development workflows and the data/infrastructure requirements associated with model training, evaluation, deployment, or integration.Experience supporting prototype or research-system development.
- Ability to develop and maintain technical architecture, interface, and system documentation.
Preferred Qualifications
- Master’s degree in computer science, engineering, data science, AI/ML, or a related discipline.
- Experience engineering systems that incorporate machine-learning or AI models.
- Experience with MLOps, model-serving architectures, feature pipelines, experiment/model management, or AI/ML lifecycle tooling.
- Experience with cloud, containerized, distributed, or hosted analytics environments.
- Experience supporting systems and data environments.
- Familiarity with cybersecurity, data governance, access-control, and system-integration requirements.
- Experience developing research prototypes that transition toward operationally relevant demonstrations.
- Familiarity with explainable AI, model provenance, data lineage, and responsible-AI engineering practices.
Equal Opportunity Employer: QAA will consider all qualified applicants’ employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other characteristic protected by law.