Chief Data Innovation Officer

5 days ago

Thiruvananthapuram, Kerala, India beBeeArtificialintelligence Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
AI Project Manager

This is a pivotal role that drives the execution of end-to-end Machine Learning (ML) and Generative AI (GenAI) projects, from ideation and experimentation to production deployment and continuous improvement. The successful candidate will define and implement data strategies that align with business goals, working in close collaboration with engineering, product, and business teams.

Responsibilities:

  • Team Leadership & Mentoring: Lead, mentor, and inspire a team of data scientists, ML engineers, and analysts to deliver high-impact AI solutions.
  • Project Ownership: Own and manage the complete lifecycle of ML and GenAI projects, including problem definition, data acquisition, model development, validation, deployment, and maintenance.
  • Data Strategy & Governance: Define and execute data strategies in alignment with organizational objectives. Ensure high standards of data integrity, security, and governance across all data assets.
  • Cross-functional Collaboration: Work closely with software engineers, product managers, and business leaders to prioritize initiatives, integrate AI solutions into products, and drive measurable business outcomes.
  • MLOps & Infrastructure: Implement and manage MLOps practices including CI/CD for models, automated monitoring, retraining pipelines, and versioning. Ensure scalable and reliable infrastructure for experimentation and production environments.
  • Innovation & Research: Stay ahead of the curve with the latest advancements in AI, GenAI, and ML. Evaluate and integrate emerging technologies such as large language models (LLMs), vector databases, and prompt engineering best practices.

Requirements:

  • Proven experience leading and managing data science teams in a production environment.
  • Strong hands-on experience in Python, and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Experience with Generative AI tools and technologies (e.g., OpenAI, LLaMA, LangChain, Hugging Face).
  • Proficient in deploying ML models on cloud platforms such as AWS, GCP, or Azure.
  • Solid understanding of MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes).
  • Strong understanding of data engineering concepts, data governance, and scalable architecture.
  • Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders.
  • Masters or PhD in Computer Science, Data Science, AI/ML, or a related field.

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