Team Lead (AI & ML)

This role requires an experienced AI and machine learning professional to lead the design, deployment, and management of on-premises large language model (LLM) infrastructure and AI pipelines within a regulated government environment. The successful candidate will be responsible for building production-grade AI systems, including Retrieval-Augmented Generation (RAG) pipelines, computer vision, and audio intelligence models, ensuring strict compliance with data sovereignty and privacy regulations. This position demands hands-on expertise in local LLM deployment, model fine-tuning, and integration of AI services into existing government software platforms, alongside leadership of a multidisciplinary AI/ML team.

Key Responsibilities

- Design and procure GPU hardware for an on-premises AI data center, installing and maintaining the full AI stack including CUDA, cuDNN, and inference runtimes such as Ollama and vLLM.
- Deploy and manage open-source foundation models (e.g., LLaMA 3, Mistral, Qwen) locally, implementing model quantization techniques to optimize inference within GPU memory constraints.
- Build and maintain a secure, zero-data-egress environment ensuring all AI processing and data remain on government servers.
- Develop and implement production-grade RAG pipelines using LangChain or LlamaIndex, including local vector databases for embedding storage and advanced document ingestion pipelines supporting multiple formats and OCR.
- Fine-tune foundation models on domain-specific datasets using LoRA/QLoRA, establish continuous learning workflows with dataset versioning, evaluation, and model lifecycle management.
- Create secure RESTful AI APIs (FastAPI or ASP.NET Core) to expose natural language processing, document summarization, intelligent search, forecasting, and anomaly detection capabilities to government platforms.
- Deploy and fine-tune computer vision models (YOLOv8/v10, RT-DETR) for video surveillance, integrating outputs with enforcement workflows and maintaining model accuracy through retraining.
- Implement local speech-to-text and diarization systems (Whisper/WhisperX, pyannote-audio) for multilingual audio intelligence, including keyword detection and integration with accountability systems.
- Design and manage SQL Server databases for AI outputs and metadata, enforcing strict data governance aligned with government cybersecurity and data residency policies.
- Lead the AI/ML team by defining roles, onboarding, and establishing MLOps practices such as experiment tracking, model versioning, and automated retraining.
- Collaborate with software, infrastructure, and operations teams to embed AI features into production environments and produce comprehensive technical documentation and reports for leadership.

Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field from a recognized university.
- Minimum of 8 years of hands-on experience in machine learning and AI development.
- Proven experience deploying and serving large language models locally, beyond API-based usage.
- Demonstrated ability to build and productionize RAG pipelines.
- Hands-on expertise with computer vision and/or audio/speech machine learning models.
- Strong systems thinking and problem-solving skills in resource-constrained, on-premises environments without cloud fallback.
- Proficiency with the following technologies and frameworks: LLaMA, Mistral, Qwen, Ollama, vLLM, llama.cpp, LangChain, LlamaIndex, Qdrant, ChromaDB, Weaviate, Milvus, PyTorch, Hugging Face Transformers, PEFT (LoRA/QLoRA), YOLOv8/v10, OpenCV, ONNX Runtime, OpenAI Whisper/WhisperX, pyannote-audio, MLflow, DVC, CUDA/cuDNN, FastAPI, ASP.NET Core, Microsoft SQL Server, Python (primary), C# (working knowledge), GPU-enabled Docker, and AI productivity tools such as Claude or GitHub Copilot.

Preferred Qualifications and Benefits

- Experience working on AI projects within government, law enforcement, or other regulated industries is strongly preferred.
- Experience in private sector entities registered with public sector regulatory authorities will also be considered.
- Commitment to data sovereignty, privacy, and compliance with government regulations.
- Strong communication skills to translate complex AI concepts into business outcomes for executive stakeholders.
- Collaborative mindset to work effectively across software development, infrastructure, and operations teams.
- Opportunity to lead and grow a specialized AI/ML team within a pioneering government AI initiative.

Applications are welcomed until October 29, 2026.