Senior Systems Engineer – Clinical NLP Research Support

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🔥 0 minutes ago

🇺🇸 United States – Remote

⏱ Part Time

🟠 Senior

⚙️ Systems Engineer

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Aptive Resources

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2012

🎖️ Defense

📦 Logistics

📣 Marketing

Defense • Logistics • Marketing

Aptive Resources is a management consulting firm based in Alexandria, Virginia, specializing in providing innovative solutions to federal government agencies, particularly in veteran and civilian health sectors. With a strong focus on performance optimization, human capital, and data analytics, Aptive aims to improve the quality and accessibility of health care services for veterans and the general public. The company utilizes technology and human-centered services to bridge divides and enhance public service delivery for multiple agencies, including Veterans Affairs, Defense, and others.

📋 Description

• Develop methods and infrastructure and refine NLP and LLM approaches to identify predictor variables for suicidal thoughts and behaviors in VA EHR clinical notes • Build and maintain custom tokenization and text-processing pipelines operating at population scale across the Million Veteran Program cohort • Extract and validate phenotypes including suicidal ideation, suicide attempts, and related exposures for gene-by-environment analyses • Prepare, document, and transfer analysis-ready datasets to the study's statistical genetics team • Manage code version control, testing, documentation, and reproducibility within the VA research computing environment • Ensure compliance with VA privacy and information security requirements for PHI and PII • Troubleshoot pipeline performance, scalability, and data quality issues and implement improvements • Coordinate with the Principal Investigator and study team and provide progress updates against project milestones • Prepare technical documentation, workflow documentation, and handoff materials

🎯 Requirements

• Bachelor's degree in computer science, engineering, data science, informatics, or a related technical field • 8+ years of experience in computer systems engineering, software development, data engineering, or technical implementation • Experience with AI/SI methods development, including developing LLM models, for EHR text evaluation within a federal research environment • Experience with the technical lifecycle of this type of research, including custom tokenization and population-scale work • Experience with programming and data pipeline development • Experience working with PHI and PII in accordance with VA privacy and security requirements • Ability to work independently in a part-time, remote role while meeting project deadlines • Ability to communicate effectively with technical and research stakeholders • Ability to obtain and maintain a public trust clearance • Legal authorization to work in the United States • Significant experience developing NLP or LLM methods for VA • Experience supporting research studies, particularly in genomics, and familiarity with programs like the Million Veteran Program • Experience with transformer-based models, model fine-tuning, or custom tokenizer development • Experience developing or validating computable phenotypes, including chart review or annotation workflows • Experience with GPU-based or high-performance computing environments • Familiarity with mental health or suicide prevention research • Experience with version control, technical documentation, and reproducible workflows • High degree of professionalism, discretion, and mature judgment in handling sensitive information • Ability to perform the stated physical requirements, including extended sitting, computer use, verbal and written communication, and occasional standing, walking, bending, or lifting up to 15 pounds

🏖️ Benefits

• Part-time schedule of 20 hours per week • 100% remote position • Potential contract extension into the next option year based on contract continuation and program needs • Opportunity to support a Department of Veterans Affairs research study and contribute to suicide prevention research • Potential to work with population-scale Million Veteran Program data and clinical NLP/LLM methods

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