Description The Government Health and Safety Solutions Operation is seeking an Applied Machine Learning Engineer. *This position requires being ONSITE IN BETHESDA, MD (with some remote opportunity)
Responsibilities
Design, develop, and maintain AI/ML solutions to support NIH grant application intake, peer review workflows, and analytics.
Develop and apply NLP and machine learning techniques (e.g., embeddings, classification, clustering, similarity analysis) for tasks such as reviewer–application matching, keyword extraction, and document analysis.
Build, evaluate, and iteratively improve machine learning models using structured and unstructured data, including text, documents, and images where applicable.
Design and implement end-to-end ML pipelines, including data ingestion, preprocessing, feature/embedding generation, model execution, evaluation, and output generation.
Debug, test, and optimize ML pipelines and tools to ensure reliable, consistent, and reproducible results.
Refactor and improve code to enhance performance, scalability, and maintainability.
Work with large and complex datasets, including implementing data validation, quality checks, and preprocessing workflows.
Conduct experiments to evaluate model performance, analyze results, and refine approaches based on quantitative and qualitative findings.
Collaborate with cross-functional teams (data scientists, analysts, program staff, and engineers) to translate business needs into practical AI/ML solutions.
Ensure reproducibility and transparency through documentation, versioning, and structured workflows.
Communicate methods, results, and limitations clearly to both technical and non-technical stakeholders.
Stay current with advancements in applied AI/ML, including NLP, embeddings, and generative AI, and evaluate their applicability to NIH use cases.
Required Qualifications
Master’s in data science, Computer Science, Computational Linguistics, or related field (or equivalent experience).
Minimum of 3–5 years of relevant experience in applied machine learning, data science, or a related field.
Strong programming expertise in Python (preferred) and/or R.
Demonstrated experience delivering end-to-end ML solutions, including model development, evaluation, and pipeline implementation.
Hands-on experience developing and applying machine learning models and workflows.
Experience with NLP techniques such as text classification, embeddings, semantic similarity, or related methods.
Experience working in cloud or shared compute environments (e.g., Azure, Biowulf, or similar).
Experience building and maintaining data processing or ML pipelines.
Experience working with real-world datasets, including data cleaning, preprocessing, and feature engineering.
Ability to debug, test, and improve complex code and analytical workflows.
Familiarity with at least one modern ML framework (e.g., PyTorch, TensorFlow, scikit-learn, or equivalent).
Strong analytical and problem-solving skills, including the ability to evaluate model performance and interpret results.
Excellent communication skills, with the ability to explain technical concepts to diverse audiences.
Preferred Qualifications
Experience with transformer-based models or large language models (LLMs), including practical applications such as text analysis or document processing.
Experience with reviewer matching, recommendation systems, or document similarity problems.
Familiarity with distributed data processing tools (e.g., Spark, Dask, Ray).
Experience with experiment tracking, model versioning, or reproducible workflows (e.g., MLflow or similar tools).
Familiarity with NIH data systems, biomedical text, or scientific research data.
Experience with medical or scientific imaging, including development or evaluation of models for detecting altered, manipulated, or AI-generated images.
Understanding of evaluation metrics (e.g., accuracy, precision/recall) and model robustness. If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares. Original Posting: April 29, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $87,100.00
$157,450.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to)
responsibilities
of the job,
education
, experience, knowledge, skills, and abilities, as well as internal eq