Full-Time Senior AI Engineer

We are seeking a Senior Machine Learning Engineer who loves solving complex challenges and making a difference. You’ll join a diverse team of epidemiologists, engineers, data scientists, front-line disease controllers, and national security practitioners.

You’ll own the vision for expanding our AI capabilities, refine our AI architecture, and develop forecasting and anomaly-detection models that directly inform critical health and defense decisions.

Responsibilities:

• Develop and refine approaches to anomaly detection, correlation, forecasting, and modeling/simulation for biological threats
• Explore both traditional and novel techniques to reveal hidden patterns, potentially with some of the following techniques:
  • Use statistical models like ARIMA and Prophet to establish clear baselines for trend and seasonality
  • Experiment with deep learning models like LSTMs or TCNs to pick up on subtle changes in time series data
  • Detect anomalies that could indicate emerging disease clusters
• Develop RAG and Agentic AI systems for Biological Threat Detection
• Fine-tune, test, and deploy large language models (LLMs)
• Design and implement retrieval-augmented generation (RAG) pipelines for domain-specific applications
• Build pipelines to ingest, clean, and validate structured and unstructured data sources
• Containerize models and services with Docker and Kubernetes, automate deployment, and monitor model performance
• Collaborate with Epidemiologists to build domain specific LLM prompts
• Work directly with customers to understand their problem space, deploy AI/ML tools, and iterate with them to ensure their mission needs are met

Experience & Qualifications:

• Bachelor’s or Master’s in Data Science, Computer Science, Statistics, or related field
• 3+ years building, working with, and shipping ML models in production
• 5+ years general software development experience
• Strong understanding and experience in data modeling, algorithms, and data transformation techniques
• Strong Python skills
• Solid foundation in statistics, probability, and time-series analysis
• Experience with relational and vector databases
• Familiarity with AWS and/or GCP
• Comfortable with Docker, Kubernetes, Git, CI/CD pipelines, and RESTful APIs
• Experience with RAG architecture and LLM integrations

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