Analytical AI Engineer - II
Core
Builds and maintains analytical and machine learning models, dashboards, and semantic layers/knowledge graphs to turn business questions into data-driven insights and make them consumable by AI Agent solutions.
Role type
mid-level IC analytical AI engineer
Builds
forecasting, classification, regression, and anomaly detection models; dashboards; semantic layers and knowledge graphs
Domain
pharmaceuticals + applied machine learning
Deliverable
production ML models | dashboards & analysis
Required skills
Python, SQL, Scikit-learn, PyTorch, TensorFlow/Keras, Databricks, PySpark, MLflow, Tableau/Power BI/Looker, RDF/OWL/SPARQL/Neo4j, statistics, experimental design
Preferred skills
Generative AI, LLM-based techniques, Azure OpenAI, AWS Bedrock, Google Vertex AI, LangChain, LangGraph, Pydantic AI, LlamaIndex, Git/GitHub, CI/CD, Agile/Scrum
Technologies
Databricks, PySpark, MLflow, VS Code, GitHub Copilot, Azure OpenAI, AWS Bedrock, Google Vertex AI, Neo4j, RDF, OWL, SPARQL
Responsibilities
Build and maintain analytical and machine learning models for forecasting, classification, regression, and anomaly detection; Collaborate with business stakeholders to translate questions into analytical tasks and run A/B tests; Build and maintain analytical dashboards and contribute to semantic layer development; Contribute to the design and development of semantic layers, ontologies, and knowledge graphs for AI Agent solutions; Build and maintain analytics and ML pipelines from data extraction through deployment; Develop and support data pipelines for analytical modeling and reporting needs; Apply Generative AI and LLM-based techniques to support analytics workflows; Track experiments and manage model versions using experiment-tracking tools; Write clean, well-documented, production-ready code for analytical modeling and pipeline development; Manage source code and version control, and contribute to CI/CD workflows
Seniority
Mid-level, hands-on IC