AI Architect

AI Architect

AI & Data Engineering – AI & Data Engineering : Data Science

Edison, New Jersey, United States

Primary Skills

Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio

Specialization

Data Science Advanced: Senior AI/ML Engineer

Job requirements

Key: Please focus on AI Architect profiles rather than Senior/Lead Data Scientist profiles and with a Pharma/Life Sciences background, with Snowflake Cortex as a good-to-have skill.

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 will be an added advantage.

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