Description

You will develop Generative AI and traditional AI platform capabilities across enterprise on-prem, GCP, and Azure environments.

Responsibilities

• Build and manage vector databases, including indexing, data ingestion, and parsing/chunking data from content management systems.
• Develop data pipelines for vector databases and Document AI on GCP and Azure.
• Deliver AI models to on-prem infrastructure and cloud platforms including Vertex AI and Azure ML.
• Automate the deployment of ML and LLM models, including model scoring and inferencing capabilities.
• Standardize data pipeline deployment and model consumption processes for multiple lines of business.
• Collaborate with product owners, DevOps, and data scientists to drive end-to-end model scoring pipelines and AI use case delivery.
• Provide SME guidance on software engineering principles and model deployment to data science teams.

Required Skills

• 5+ years of Python experience.
• 5+ years of big data experience using Big Query and Hadoop.
• 3 years of experience in AI/ML (MLOps).
• 2+ years of experience developing APIs using Python and FastAPI.
• Experience with GCP and Azure.
• Any Graduate degree.

Preferred Skills

• 1+ year of experience with LLMs, Generative AI, or Vector Databases.
• Experience developing APIs on GCP, Azure, or API Gateways.

Key Skills

Education

Any Graduate