NLM Deep Learning Software Developer

Bioinformatics Specialist And Developer (Sme) I - Iii

Lexical Intelligence provides software and services related to processing large-scale biomedical information sources. Our natural language processing (nlp) and analytics software is used by policy and decision makers to evaluate and prioritize current and emerging areas of research.

We are looking for bioinformatics specialists and developers (smes) i - iii to work within the national library of medicine (nlm), lister hill national center for biomedical communications (lhncbc), nih campus, bethesda, md. The smes will have experience in biomedical informatics research and development, software development and data analytics, and clinical data systems and statistical analysis. The smes will have a firm understanding of ai/ml methodologies, nlp techniques, and translational science informatics. The smes shall be able to work well within a team of multidisciplinary researchers, data scientists, software engineers, and federal staff across nlm divisions and nih institutes. The selected applicants will be subject to a pre-employment background and reference check.

Level Descriptions

Sme Level I - Professionals work under general supervision and are responsible for implementing technical solutions, conducting data analysis, and supporting software development projects. They should have previous experience in computer science or a related field and demonstrated high proficiency in python. They participate in computational language processing including rule-based models, transformer models, and large language models for document-level summarization and data extraction from unstructured sources. Focus areas include implementation and execution of biomedical informatics projects under guidance, contributing to software development and data analysis tasks, and supporting research initiatives.

Sme Level II - Professionals work with greater independence and are responsible for leading technical initiatives, mentoring junior staff, and managing complex analytical projects. They should have experience in artificial intelligence, machine learning, information retrieval, and data mining. At this level, professionals are expected to provide technical oversight and coordinate efforts across development teams. Focus areas include leading technical components of projects, designing and implementing complex systems, mentoring junior team members, and exercising greater autonomy in decision-making and project execution.

Sme Level III - Sme Level III professionals serve as technical leaders and should have at least 7 years of experience designing, deploying, and managing analytical projects that address problems in large-scale biomedical knowledge discovery. Their expertise includes categorization of biological entities, scientific document classification, parsing scientific content, and natural language processing and analysis. They provide strategic direction, manage complex projects, and serve as subject matter experts for the organization and clients. Focus areas include providing strategic technical leadership, driving innovation in research and development, serving as subject matter expert for complex biomedical informatics challenges, leading cross-functional initiatives, and contributing to scientific publications.

Required Qualifications

Sme Level I

4+ years of relevant experience in biomedical informatics, data science, or software development

Master's degree in computer science, biomedical informatics, data science, bioinformatics, or related fields

Sme Level II

8+ years of relevant experience in biomedical informatics, data science, or software development

Master's degree in computer science, biomedical informatics, data science, bioinformatics, or related fields

Sme Level III

6+ years of relevant experience in biomedical informatics, data science, or software development

Doctoral degree (ph.d.) in computer science, biomedical informatics, data science, bioinformatics, or related fields

Required Qualifications (All Levels)

Experience and education requirements as specified above (commensurate with sme level i–iii)

Proficiency in one or more programming languages including python, java, c++, r, javascript, sql, or matlab

Experience with machine learning (ml), deep learning (dl), and/or natural language processing (nlp) methods

Experience with software development lifecycle (sdlc) including analysis, design, implementation, testing, deployment, and maintenance

Familiarity with fisma requirements and secure coding best practices (owasp, us-cert standards)

Strong written and oral communication skills, with the ability to document technical work for both internal and external audiences

Preferred Qualifications

Experience with clinical data systems, including storage, searching, analyzing, and viewing of health-related datasets (e.g., ehr, claims data)

Proficiency in statistical methods such as logistic/multinomial regression, cox regression, predictive modeling, and/or large language models (llms)

Experience with data visualization tools such as tableau, splunk, google analytics, databricks, sas, python, spark sql, r, or powerbi

Knowledge of cloud computing platforms (aws, google cloud, azure) including iaas, paas, saas, and ci/cd configurations

Experience with containerization and orchestration tools such as docker, kubernetes, anthos, or openshift

Familiarity with web development standards including section 508 compliance, responsive design, and restful architecture

Experience supporting biomedical research projects in areas such as computational biology, ai-driven clinical research, image processing, or translational science

Familiarity with agile/scrum project management frameworks

Experience with database technologies such as mysql, mongodb, ms sql, postgresql, or elasticsearch

Knowledge of nih/nlm/hhs security frameworks, including nist sp 800-53, nist sp 800-171, fips 199/200, and authority to operate (ato) processes

Experience with data interoperability, data harmonization, data linkage, and longitudinal clinical studies

Familiarity with tools such as jupyter notebooks, github copilot, chatgpt, or etl workflows

Responsibilities

Participate in all phases of software, application, and tool development and maintenance, including inception, analysis, design, implementation, testing, deployment, and maintenance

Support nlm's mission to advance data science, open science, biomedical informatics, biomedical discovery, and translational science

Develop and maintain systems and databases for the secure storage of personal health information (phi), personally identifiable information (pii), and personal information (pi), including support for the fisma-moderate fehrddi environment

Conduct statistical analysis including regression analysis, predictive modeling (ml/dl), and synthesis of research findings using ai tools (llm), and extract and standardize text into categorical data using nlp techniques

Perform data management functions including data collection, standardization, imputation, harmonization, integration, and interoperability

Design and implement ai and other technology projects, including for the center for clinical observational investigations

Support the development of web-based and user interfaces based on user needs analyses, design prototyping, and evaluation using graphic design, data visualization, and user-centered design techniques; all interfaces must meet section 508 compliance requirements

Leverage commercial cloud computing services (gcp, aws, azure) to make tools publicly available

Conduct software testing and quality control employing automated testing environments and configuration management

Document technical project requirements, timelines, and development schedules for internal and external dependencies

Generate status updates for management and stakeholders, identifying progress, changes, and potential risks

Conduct applied research activities using modern methodologies including user surveys, stakeholder interviews, and usability testing

Ensure all developed software is documented for internal and external users and future maintenance

Ensure system architecture is secure, extensible, and able to integrate with existing internal or external systems

Ensure outputs are compliant with hhs, nih, nlm, and lhncbc security and operational policies

Utilize agile and scrum project management frameworks to ensure project deliverables are met within defined timelines

Ensure compliance with organizational security and privacy policies, protect sensitive data and systems, report security incidents, and participate in required cybersecurity training

Implement best practices related to access control, data handling, and risk mitigation within the scope of assigned duties

Collaborate with nlm's office of computer and communications systems (occs) and lhncbc's scientific computing branch (scb) to ensure system compliance with security policies

Salary and Benefits: We offer a competitive salary and a generous benefits package, including at no cost: full health and dental for you and your dependent