AI/ML Software Engineer
$113,000–$188,000 year
RemoteUnited States
Job Summary
Design, develop, and deploy end-to-end AI/ML applications, including Retrieval-Augmented Generation systems, AI chatbots, and agentic workflows for federal clients. Construct scalable data pipelines to process and feed structured and unstructured data into models, while developing machine learning solutions for risk scoring, anomaly detection, and predictive analytics. Apply graph analytics and entity resolution techniques to uncover hidden relationships in large datasets supporting fraud detection and trafficking investigations. Implement NLP capabilities to extract entities and indicators from unstructured text, and build REST APIs to serve model inferences within AWS cloud environments using infrastructure-as-code. Collaborate with cross-functional teams to prototype solutions for mission-critical challenges in data triage and automated discovery.
Required Qualifications
- Ability to Obtain Public Trust
- Approved adjudication of their PUBLIC TRUST prior to onboarding
- Active Public Trust or Suitability (preferred but treated as required for qualification context)
- Bachelor's degree
- Minimum SIX (6) years of hands-on experience with Python and JavaScript and/or TypeScript
- Master's degree OR Industry Certification (substitutable for up to two years of relevant professional experience)
- Strong hands-on experience with Python for AI/ML application development, data engineering, data analysis, and model implementation
- Proven experience developing RAG applications, including implementing re-ranking strategies
- Experience building AI chatbots or conversational agents
- Hands-on experience with AI application frameworks such as LangChain, Haystack, crewAI, or similar
- Strong knowledge of core Python data science and ML libraries, including NumPy, Pandas, Scikit-learn, NLTK, and OpenCV
- Demonstrated experience developing and applying machine learning models for classification, clustering, risk scoring, anomaly detection, and pattern recognition
- Experience with graph analytics, network analysis, and relationship discovery across complex datasets
- Experience with entity resolution, record linkage, deduplication, identity matching, or similar data matching techniques
- Experience applying NLP techniques such as named entity recognition, text classification, semantic search, information extraction, topic modeling, and relationship extraction
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow
- Experience with search technologies such as Elasticsearch or OpenSearch
- Experience with relational databases, such as PostgreSQL or Oracle DB, and in-memory analytics databases, such as DuckDB
- Strong knowledge of SQL and data modeling techniques
- Experience with cloud SDKs, such as Boto3 for AWS
- Ability to work with large, disparate datasets and uncover hidden patterns, relationships, anomalies, and risk indicators
- Strong analytical, problem-solving, and communication skills, with the ability to translate mission needs into practical AI/ML solutions
Desired Qualifications
- Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred
- Familiarity with agentic AI frameworks such as AWS Strands Agents, PydanticAI, or similar
- Advanced prompt engineering skills for complex tasks beyond code generation
- Experience with asynchronous Python development
- Experience with MCP servers and tool calling within agentic workflows
- Knowledge of GPU-accelerated computing, CUDA, and hardware optimization for running ML models efficiently
- Experience with graph databases or graph processing frameworks such as Neo4j, Amazon Neptune, TigerGraph, NetworkX, GraphFrames, or similar
- Experience supporting fraud detection, trafficking detection, investigations, intelligence analysis, case management, or law enforcement-adjacent mission environments
- Experience building explainable AI/ML models that support analyst review, investigative workflows, and auditability
- Experience integrating AI/ML capabilities into federal cloud environments while following security, privacy, and compliance best practices
- Familiarity with geospatial analytics, temporal analytics, link analysis, or behavioral pattern detection
- Experience designing AI/ML solutions that support human-in-the-loop review, case prioritization, and investigative decision support
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