NTT DATA - Charlotte, NC

posted 2 months ago

Full-time - Mid Level
Charlotte, NC
10,001+ employees
Professional, Scientific, and Technical Services

About the position

As an AI/ML Engineer at NTT DATA Services, you will be instrumental in implementing advanced solutions that leverage artificial intelligence and machine learning technologies. Your role will involve working closely with clients to understand their needs and deliver tailored solutions that enhance their operational capabilities. You will be part of a dynamic team that is focused on developing both Generative AI and Traditional AI platform capabilities across enterprise on-premises and cloud environments. This position requires a blend of technical expertise in AI/ML and strong consulting skills to ensure successful project outcomes and high levels of client satisfaction. In this role, you will be responsible for the delivery of AI models to both on-premises infrastructure and cloud platforms, including GCP-Vertex AI and Azure ML. You will collaborate with data scientists to optimize scoring pipelines and build automation capabilities for deploying machine learning models and large language models (LLMs) on enterprise platforms. Your work will also involve standardizing data pipeline deployment and ensuring model consumption across various lines of business (LOBs). You will engage with product owners, DevOps teams, and support teams to define and drive end-to-end model scoring pipelines, participating in daily standups to track progress and address challenges. Additionally, you will provide subject matter expert (SME) guidance to data science teams on software engineering principles and model deployment strategies. Your contributions will be critical in driving AI use case delivery from inception to completion, ensuring that all processes align with standardized platform capabilities. You will also play a key role in supporting production issues, partnering with production support teams to resolve challenges as they arise.

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).
  • Collaborate with Data scientists to optimize the scoring pipeline.
  • Build 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.

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.

Nice-to-haves

  • Document AI, Agent Builder/GCP search/conversation / Dialogflow
  • LLM, Generative AI (developing capabilities or dev/ops)
  • Developing of API on GCP/Azure/API Gateways
  • Vector Database and Model Development
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