Lead AI/ML Engineer

2 weeks ago


Chennai, India Pickyourtrail Full time

We are seeking an experienced AI leader to spearhead our AI initiatives, ensuring AI is deeply integrated into our business processes. The role will focus on optimizing workflows, enhancing operational efficiencies, and improving customer and sales experience. You will lead the development and deployment of AI solutions to enhance efficiency, improve revenue, and revolutionize our customer experience.


Responsibilities

AI Strategy Development & Leadership

  • Define and lead the overall AI strategy, ensuring alignment with business goals and outcomes
  • Partner with cross-functional teams (Product, Sales, Engineering, Operations) to identify AI-driven opportunities to improve efficiency, accuracy, and speed in workflows across the organization

Operational Efficiency & Automation

  • Implement AI-driven solutions to reduce the time needed to ramp up Sales and Customer Experience (CX) teams.
  • Leverage AI for workflow automation (e.g., auto-labeling customer issues, optimizing ticket resolution).
  • Collaborate with engineering teams to enhance booking experience for customers

Revenue Growth & Customer Experience

  • Develop AI solutions that optimize revenue generation, including personalized recommendations for customers and enhanced itinerary creation.
  • Use AI to drive improvements in customer engagement, reducing friction in the online booking experience.

Data Strategy & Integration

  • Utilize both relational and non-relational databases to implement robust AI solutions.
  • Ensure effective data governance, security, and scalability as AI becomes a core component of the business.


Ideal Candidate Profile


  1. 5+ years of experience in AI/ML roles; Proven track record of implementing AI/ML solutions that have delivered measurable impact on efficiency and revenue.
  2. Good understanding of architecture, design and implementation of LLMs
  3. Expertise in Python, TensorFlow, PyTorch, or other relevant AI/ML frameworks for data analysis / machine learning
  4. Expertise in deep learning algorithms and frameworks such as TensorFlow, PyTorch, or Keras
  5. Strong knowledge of NLP techniques and libraries (e.g., NLTK, spaCy, Transformers)
  6. Experience with cloud platforms (AWS, Google Cloud, or Azure) for deploying AI solutions
  7. Hands-on experience with computer vision libraries (OpenCV, scikit-image)
  8. Proficiency in SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra)
  9. Experience with containerization and orchestration tools (Docker, Kubernetes)
  10. Knowledge of MLOps practices and tools (MLflow, Kubeflow, or similar)
  11. Understanding of RESTful APIs and microservices architecture
  12. Knowledge of recommendation systems and personalization algorithms
  13. Understanding of time series analysis and forecasting techniques
  14. Excellent communication skills to articulate AI concepts to both technical and non-technical stakeholders



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