AI Architect - R01566870
HybridEdison, New Jersey, United States
Job Summary
Develop scalable AI/ML solutions by designing and deploying machine learning models, conducting feature engineering, and managing the AI application lifecycle using Snowflake and Snowflake Cortex. Lead initiatives in Generative AI, including Large Language Models, Retrieval-Augmented Generation, and AI agents, while collaborating with cross-functional teams to translate business requirements into data-driven outcomes. This role requires a Pharma/Life Sciences background with strong proficiency in SQL and Python, alongside experience in MLOps and vector databases. Located in Plainsboro, NJ, this hybrid position mandates a minimum of four days onsite per week.
Required Qualifications
- AI Architect
- Pharma/Life Sciences/Healthcare background
- Experience in Data Science, Machine Learning, Artificial Intelligence, or related fields
- Strong proficiency in SQL and Python
- Hands-on experience in data analysis, feature engineering, model development, evaluation, and deployment of machine learning solutions to solve business problems
- Good understanding of Generative AI concepts, including Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and emerging AI frameworks and protocols such as MCP
- Ability to work with structured and unstructured data, build scalable AI/ML solutions, and collaborate with cross-functional teams to translate business requirements into data-driven outcomes
- Strong problem-solving, analytical, and communication skills
- Demonstrated willingness and enthusiasm to learn new technologies, tools, and emerging AI/ML trends in a fast-evolving landscape
- Hybrid with min 4 days onsite per week
- Location: Plainsboro, NJ
Desired Qualifications
- Experience with Snowflake data platform
- Exposure to Snowflake AI capabilities and Cortex services
- Familiarity with MLOps, model deployment, monitoring, and AI application lifecycle management
- Knowledge of data warehousing, data engineering concepts, and API integrations
- Exposure to GenAI application development, vector databases, semantic search, and AI orchestration frameworks
- Lifesciences experience
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