Data Scientist

Charlotte, NC (Onsite)

Key Responsibilities:

• Participate in developing Generative Al & Traditional Al Platform Capabilities on enterprise on- prem and cloud platforms.
• Responsible for Al model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex Al, Azure ML).
• Collaborating with Data scientist to optimize the scoring pipeline.
• Building automation capabilities to deploy ML Models and LLM Models on the enterprise on-prem platform and cloud platform. I
• Build and Deploy capabilities for automating model scoring/Inferencing of ML models and LLMs.
• Build and Deploy capabilities for data pipeline deployment standardization and model consumption by multiple LOBS.
• Collaborate with product owners, devOps team, data scientists, support teams to define and drive end to end model scoring pipelines.
• Participate in day-to-day stand ups for platform capability build.
• Provide SME guidance for data science teams on software engineering principles, model deployments, platform capabilities.
• Drive Al use case delivery end to end collaborating with Data scientists, Data Engineers, LOB Technology using standardized platform processes and capabilities.
• Support Production Issues partnering with production support.

Requirements:

· 5 Years of Python Experience.

· 5 Years of big data experience needed (Big Query, Hadoop)

· 3 Years of experience in AIML area (MLOps).

· 2 years of experience in developing APIs using Python/FastAPI.

· Good to have 1 years of experience in LLM, Generative AI (developing capabilities or dev/ops)

· Good to have experience in developing of API on GCP/Azure/API Gateways

· Good to have 1 years of experience in Vector Database, Model development would be added benefit.