AI Lead

We are looking for a
hands -on and visionary AI Lead to spearhead all AI initiatives
within our organisation. Candidate will lead a focused team comprising
1 Data Scientist, 1 ML Engineer and 1 Intern, while also being
directly involved in designing and implementing AI solutions.
The role involves identifying impactful AI use cases, conducting
research, proposing tools and deploying AI models into
production to enhance products, processes and user
experiences.

The candidate will work across
diverse domains such as NLP, computer vision, recommendation
systems, predictive analytics and generative AI. The position
also covers conversational AI, intelligent automation and
AI -assisted workflows for the AEC industry. A strong
understanding of ethical and responsible AI practices is
expected.

Key
Responsibilities:

• Lead AI research,
  tool evaluation and strategy aligned with business needs
  
• Build and deploy
  models for NLP, computer vision, generative AI, recommendation
  systems and time -series forecasting
  
• Guide the
  development of conversational AI, intelligent
  automation and design -specific AI tools
  
• Mentor and manage a
  small team of AI/ML professionals
  
• Collaborate with
  cross -functional teams to integrate AI into products and
  workflows.
  
• Ensure ethical use
  of AI and compliance with data governance
  standards.
  
• Oversee lifecycle
  of AI models from prototyping to deployment and
  monitoring.
  

Qualifications and
Experience Required:

• BE/BTech or
  ME/MTech degree in Computer Science, Data Science,
  Artificial Intelligence or related field
  
• Certifications in
  AI/ML, cloud AI platforms or responsible AI practices are a
  plus
  

• 4–5 years of
  experience in AI/ML projects
  
• Strong programming
  skills in Python (must -have), R is a plus
  
• Experience with TensorFlow, PyTorch, Scikit -learn, OpenCV
  
• Familiarity with NLP tools like spaCy, NLTK and Hugging Face
  Transformers
  
• Backend integration
  using FastAPI or Flask
  
• Experience
  deploying models using Docker, Kubernetes and cloud
  services like AWS, GCP or Azure ML
  
• Use of MLflow, DVC for experiment
  tracking and model versioning
  
• Strong data
  handling with Pandas, NumPy and visualisation
  using Matplotlib , Seaborn
  
• Working knowledge
  of SQL, NoSQL and BI tools
  like Power BI or Tableau
  
• ​Familiarity with AEC, design
  workflows  or other
  data -rich industries
  
• Experience
  collaborating with domain
  experts to frame and solve
  AI problems
  

• Proven ability to
  lead small AI/ML teams.
  
• Strong
  communication and stakeholder management
  
• Familiarity with
  ethical AI principles and data privacy frameworks
  
• Ability to
  translate business problems into AI solutions and
  deliver results