Build and ship AI-assisted tools and workflow automations for high-volume operations teams, reducing manual effort and analyst burden while improving decision quality through rapid prototyping and iteration.
AI Architect - R01570927
📜 Description
- Analyze data, engineer features, and develop, evaluate, and deploy machine learning solutions for business problems.
- Apply generative AI concepts, including LLMs, prompt engineering, RAG, and AI agents.
- Build scalable AI/ML solutions using structured and unstructured data.
- Collaborate with cross-functional teams to translate business requirements into data-driven outcomes.
- Keep current with emerging AI/ML technologies, tools, and trends.
🛠️ Requirements
- Experience in data science, machine learning, artificial intelligence, or a related field.
- Strong proficiency in SQL and Python.
- Understanding of LLMs, prompt engineering, RAG, AI agents, and emerging frameworks and protocols such as MCP.
- Strong problem-solving, analytical, and communication skills.
- Preferred: experience with Snowflake, Snowflake AI capabilities, and Cortex services.
- Preferred: familiarity with MLOps, model deployment and monitoring, and AI application lifecycle management.
- Preferred: knowledge of data warehousing, data engineering, API integrations, vector databases, semantic search, and AI orchestration frameworks.
- Life sciences experience preferred.
Full job description
- Experience in Data Science, Machine Learning, Artificial Intelligence, or related fields, with strong proficiency in SQL and Python. (preferably SQL)
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, with a demonstrated willingness and enthusiasm to learn new technologies, tools, and emerging AI/ML trends in a fast-evolving landscape.
Preferred Qualifications
-
- Experience with Snowflake data platform; exposure to Snowflake AI capabilities and Cortex services is prefered
- 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.
- With Lifesciences experience preferred
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