Overview
Accepts corp to corp applications
Contract - W2
Contract - 6 month(s)
Skills
Python
hadoop
GenAI
Big Query
AIML
MLOps
Python/FastAPI
Job Details
We are Hiring for Gen AI engineer in Charlotte, North Carolina (100% onsite)
Role : Senior Gen AI engineer
Client Location : Charlotte, North Carolina (100% onsite)
Hire Type (FTE/Contract): Contract
Project Duration: 6 months
Notice Period :Immediate joiners
Client Location : Charlotte, North Carolina (100% onsite)
Hire Type (FTE/Contract): Contract
Project Duration: 6 months
Notice Period :Immediate joiners
Key Requirements:
8+ 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+year of experience in LLM, Generative AI (developing capabilities or dev/ops)
Good to have Experience in developing of API on Google Cloud Platform/Azure/API Gateways
Good to have 1+year of experience in Vector Database, Model Development would be added benefit.
Key Responsibilities:
Participate in developing Generative AI & Traditional AI Platform Capabilities on enterprise on-prem and cloud platforms.
Responsible for AI model delivery to on-prem infrastructure and cloud platforms (Google Cloud Platform-Vertex AI, 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.
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 standups for platform capability build.
Provide SME guidance for data science teams on software engineering principles, model deployments, platform capabilities.
Drive AI 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.
Participate in developing Generative AI & Traditional AI Platform Capabilities on enterprise on-prem and cloud platforms.
Responsible for AI model delivery to on-prem infrastructure and cloud platforms (Google Cloud Platform-Vertex AI, 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.
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 standups for platform capability build.
Provide SME guidance for data science teams on software engineering principles, model deployments, platform capabilities.
Drive AI 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.
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