Guidehouse is seeking a Lead AI/ML Engineer to support mission-critical initiatives for Defense and Security clients by designing and operationalizing advanced AI solutions that leverage large language models (LLMs), retrieval systems, and secure, scalable inference pipelines to enable data-driven decision-making.
Requirements
- Expertise in PyTorch, HuggingFace Transformers, vLLM, DeepSpeed, or equivalent frameworks.
- Strong background in retrieval systems, embeddings, RAG pipelines, vector databases, and long‑context optimization.
- Experience implementing MLOps workflows, evaluation frameworks, drift detection, and responsible‑AI safeguards.
- Experience delivering ML systems in secure federal environments subject to FedRAMP High or RMF controls.
- Minimum of Eight (8) years of experience in AI/ML engineering with 4+ years focused on NLP, LLMs, or MLOps.
- Experience with citation‑grounding pipelines, evidence‑verification workflows, or structured model‑output evaluation.
- AWS Machine Learning Specialty, Solutions Architect Professional, or GPU Compute certifications.
Responsibilities
- Serves as the lead AI/ML engineer responsible for developing, optimizing, and operationalizing advanced LLM-driven workflows for the FBI adjudication platform.
- Leads development of dual-path model operations supporting self-hosted open‑weight LLMs in AWS GovCloud and FedRAMP‑High managed endpoints.
- Designs and maintains continuous learning systems including SFT, LoRA/QLoRA adapters, dataset curation, automated evaluation suites, hallucination detection, bias evaluation, and model drift monitoring.
- Ensures all model operations adhere to FedRAMP High, RMF, CJIS, and FBI ATO requirements, including controls for logging, access, explainability, evidence provenance, and data protection.
- Develop and maintain LLM inference pipelines supporting long‑document reasoning, multi‑document fusion, entity extraction, anomaly detection, SEAD‑4 scoring, and structured memo generation.
- Implement distributed GPU inference frameworks (vLLM, TGI, DeepSpeed, Sagemaker) and optimize workloads with KV caching, tensor parallelism, dynamic batching, and memory efficiency strategies.
- Develop output‑validation routines enforcing schema correctness, key‑evidence referencing, structured scoring, and quality controls for all model‑generated adjudicative content.
Other
- An ACTIVE and MAINTAINED 'TOP SECRET' Federal or DoD security clearance and obtained and maintain TS/SCI clearance.
- Minimum of Eight (8) years of experience in AI/ML engineering with 4+ years focused on NLP, LLMs, or MLOps.
- Bachelor's Degree or Four (4) additional Years of experience in lieu of degree.
- Up to 10% travel required.
- Collaboration with adjudicators, SEAD‑4 SMEs, and mission stakeholders to translate adjudicative logic into prompts, features, and structured model outputs.
