Artificial Intelligence (AI) Engineer II (2316)

Responsibilities: • Evaluate machine learning processes and select appropriate models • Collect and analyze large datasets to train AI models • Develop and deploy AI algorithms and systems • Collaborate with cross-functional teams to establish goals for AI processes • Test and validate AI models to ensure accuracy and effectiveness • Manage data and project infrastructure • Stay updated on the latest AI developments and technologies Qualifications: • Master’s degree in Computer Science, Engineering, or a related field • Proven experience as an AI Engineer or in a similar role • Strong programming skills in Python, R, or Java • Experience with machine learning frameworks and libraries • Excellent analytical and problem-solving abilities • Effective communication and collaboration skills Key Expertise: • Large Language Models (LLMs): Hands-on experience fine-tuning, adapting, and deploying LLMs, including prompt engineering, embeddings, and context management • LLM Application & System Architecture: Ability to design and implement production-grade LLM solutions, such as RAG pipelines, agents, and tool/function-calling systems • Production MLOps & Model Lifecycle Management: Experience with end-to-end ML lifecycle including CI/CD, deployment, monitoring, versioning, and performance/cost optimization • Advanced Python & Software Engineering: Building scalable, testable APIs and services that integrate ML/LLM models into enterprise systems • Cloud-Based Scalable ML Infrastructure: Experience with AWS, Azure, or GCP, including containerization (Docker), orchestration (Kubernetes), and GPU-based ML workloads Additional Requirements: Standard 5-panel drug screen required