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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 (GCP-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.
Key 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.
- 1+ year of Document AI, Agent Builder/GCP search/conversation / Dialogflow – Nice to have
- 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 GCP/Azure/API Gateways
- Good to have 1+year of experience in Vector Database, Model Development would be added benefit.
Job Role : AI-ML Engineer
Location: Frisco, TX
Full Time
