Key Responsibilities
- Define and implement AI/ML strategy aligned with product vision and business objectives
- Develop and deploy generative AI, agentic AI, and classical ML models for scalable solutions
- Lead ML Ops pipelines for model training, deployment, monitoring, and optimization
- Collaborate with cross-functional teams to integrate AI solutions into existing systems
- Mentor and upskill team members to foster innovation and technical excellence
- Optimize models for performance, scalability, and cost-efficiency in production environments
Requirements
- 4–8+ years of AI/ML development experience with production deployment expertise
- Proficiency in Python and libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, and Hugging Face
- Experience with generative AI models (e.g., GPT, DALL-E) and agentic AI frameworks
- Familiarity with ML Ops tools (MLflow, Kubeflow, TFX, SageMaker) and cloud platforms (AWS, Azure, GCP)
- Strong leadership skills to guide teams and align AI initiatives with business goals