- Company Name
- PHC Global
- Job Title
- Senior AI / ML Engineer
- Job Description
-
**Job Title**
Senior AI Engineer
**Role Summary**
Design, develop, and deploy machine‑learning solutions for biothreat intelligence, integrating anomaly detection, forecasting, and domain‑specific LLMs. Own the AI architecture, from data ingestion to production deployment, and collaborate with epidemiologists, security analysts, and clients to deliver actionable insights.
**Expectations**
- Own end‑to‑end AI product lifecycle: vision, design, implementation, validation, and optimization.
- Deliver production‑ready models that support rapid detection, attribution, and risk quantification of emerging biological threats.
- Communicate technical solutions to non‑technical stakeholders and iterate based on client feedback.
- Maintain model performance, scalability, and reliability; demonstrate continuous improvement.
- Participate in occasional client engagements, including on‑site support if required.
**Key Responsibilities**
- Build and refine anomaly‑detection, correlation, and forecasting models (ARIMA, Prophet, LSTM, TCN).
- Quantify prediction uncertainty to inform risk‑aware decision‑making.
- Design RAG pipelines and agentic AI systems for domain‑specific biological threat detection.
- Fine‑tune, unit test, and deploy LLMs for domain NLP tasks; optimize prompts and context engineering.
- Develop data pipelines for structured and unstructured inputs (sequencing, sensor, lab reports).
- Containerize models with Docker, orchestrate with Kubernetes, automate CI/CD, and monitor model drift/performance.
- Collaborate with domain experts to craft LLM prompts and validate outputs.
- Engage clients to understand requirements, deploy solutions, and ensure deliverables meet mission needs.
**Required Skills**
- 3+ years shipping ML models in production; 5+ years full‑stack software development.
- Strong Python programming; experience with SQL, vector databases, and time‑series libraries.
- Expertise in statistics, probability, and time‑series analysis.
- Proficiency with AWS and/or GCP, Docker, Kubernetes, Git, CI/CD, and RESTful APIs.
- Experience with RAG architectures, LLM integrations, and retrieval‑augmented generation.
- Excellent communication; capable of explaining technical concepts to diverse audiences.
- Self‑motivated, collaborative, and able to thrive in fast‑moving environments.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field.
- Security clearance‑eligible (or willingness to obtain).