Chief AI Innovation Officer

2 days ago

Varanasi, Uttar Pradesh, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

We are seeking a visionary Lead AI Engineer to spearhead the design, development and deployment of advanced machine learning solutions.

In this leadership role, you will guide a team of AI/ML engineers, contribute hands-on to critical technical challenges and collaborate with cross-functional teams to deliver impactful AI products.

This role is ideal for someone who thrives at the intersection of innovation, engineering rigor and business value.

Key Responsibilities:

  • Technical Leadership: Lead the architecture, development and deployment of machine learning models and AI systems across a range of use cases.
  • Model Development: Design, train and optimize supervised, unsupervised and deep learning models using frameworks like PyTorch, TensorFlow and XGBoost.
  • Mentorship: Coach and mentor a team of ML engineers and data scientists; foster a culture of innovation, ownership and continuous learning.
  • Project Management: Drive planning, execution and delivery of AI/ML projects, ensuring alignment with business objectives and technical feasibility.
  • System Design: Architect scalable, secure and high-performance ML pipelines and services using cloud-native tools and MLOps best practices.
  • Collaboration: Work closely with product managers, data engineers and DevOps teams to translate business problems into AI-driven solutions.
  • Code Quality & Governance: Establish standards for model quality, reproducibility, documentation, versioning and monitoring.
  • Innovation: Stay current with research and industry trends in ML/AI, evaluate new tools and introduce state-of-the-art solutions where applicable.

Required Skills and Experience:

Education: Bachelor's or Master's in Computer Science, Machine Learning, Data Science or related technical field.

Experience: 6-10+ years of experience in software engineering or AI/ML, with at least 2+ years in a technical leadership role.

Technical Expertise:

  • Strong programming skills in Python and experience with ML libraries such as Scikit-learn, TensorFlow, PyTorch, Hugging Face.
  • Deep understanding of ML fundamentals: feature engineering, model evaluation, optimization and deployment.
  • Proficiency in designing and building data pipelines, real-time processing and model inference systems.
  • Experience with cloud platforms (AWS, GCP or Azure), containerization (Docker, Kubernetes) and CI/CD pipelines.
  • Familiarity with MLOps tools (e.g. MLflow, DVC, Airflow, SageMaker) and vector databases (e.g. FAISS, Pinecone).

Preferred Qualifications:

Hands-on experience with LLMs, RAG pipelines or generative AI applications.

Familiarity with agentic AI frameworks (LangChain, CrewAI, AutoGPT).

Domain expertise in fintech, healthtech, HR tech or industrial automation.

Contributions to open-source AI/ML projects or published research.

Knowledge of responsible AI practices, explainability (XAI) and model governance.

Soft Skills:

Strong leadership and team-building skills.

Clear and persuasive communication with both technical and non-technical stakeholders.

Strategic thinker with attention to detail and a bias for action.

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