Generative AI Innovation Leader

4 days ago


Hyderabad, Telangana, India Grid Dynamics Full time
Job Description:

At Grid Dynamics, we are seeking an experienced Generative AI Innovation Leader to spearhead the development and deployment of our cutting-edge generative AI applications. This is a unique opportunity to leverage your expertise in deep learning and reinforcement learning to drive business value and innovation.

Key Responsibilities:
  • Develop and communicate the company's generative AI vision and strategy, ensuring alignment with organizational objectives.
  • Architect scalable systems for deploying generative AI applications, integrating them with existing technology stacks.
  • Provide leadership and mentorship to teams, promoting best practices in generative AI development and deployment.
  • Oversee the end-to-end process of generative AI solutions from ideation through delivery and operationalization.
  • Work closely with stakeholders to identify opportunities for AI-driven solutions and streamline change management processes.
  • Monitor, optimize, and troubleshoot production systems to maintain high performance of AI applications.
  • Design and manage continuous integration and continuous deployment pipelines for generative AI solutions.
  • Define and deliver quality API access for various generative AI services.
Required Qualifications:
  • Bachelor's degree with 8+ years of experience; or Master's degree with 7+ years of experience; or PhD with 3+ years of experience in relevant fields (e.g., Computer Science, Engineering).
  • Proven experience as an Enterprise Architect or Solution Architect focusing on AI/ML and generative AI technologies.
  • Proficiency in programming languages such as Python , R , or Java .
  • Hands-on experience with machine learning frameworks like TensorFlow , PyTorch , and libraries for deep learning .
  • Strong understanding of generative AI techniques, including deep generative models and reinforcement learning.
  • Expertise in CI/CD pipeline design and management, particularly in the context of generative AI.
  • Familiarity with cloud platforms (AWS, Azure) and containerization tools (Docker, Kubernetes).
  • Experience with data handling, including data cleansing, preprocessing, and storage solutions (e.g., Snowflake).
  • Knowledge of large language models (LLMs) such as Microsoft Azure OpenAI (e.g., ChatGPT).


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