Description :

Key Responsibilities :

- Solution Architecture : Design and architect end-to-end AI/ML solutions for complex business problems.

- Model Development : Build, train, and optimize machine learning models, including deep learning and generative AI models.

- GenAI Expertise : Develop and integrate Generative AI solutions (LLMs, multimodal models) into enterprise applications.

- Agentic Frameworks : Implement agent-based architectures for autonomous decision-making and workflow automation.

- Technical Leadership : Mentor and guide engineering teams, ensuring best practices in AI/ML development and deployment.

- Collaboration : Work closely with product managers, data scientists, and stakeholders to align AI initiatives with business goals.

- Performance Optimization : Ensure scalability, reliability, and efficiency of AI systems in production environments.

Required Skills & Qualifications :

- Experience : 8 - 10 years in AI/ML engineering with proven track record of delivering production-grade solutions.

- Architecture Expertise : Prior experience in architecting AI/ML systems and pipelines.

- Programming : Proficiency in Python, TensorFlow, PyTorch, and related ML frameworks.

- GenAI Knowledge : Strong understanding of LLMs, prompt engineering, and generative AI technologies.

- Agentic Frameworks : Hands-on experience with frameworks like LangChain, AutoGen, or similar.

- Cloud & MLOps : Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.

- Soft Skills : Excellent problem-solving, communication, and leadership abilities.

Preferred Qualifications :

- Experience with multimodal AI systems (text, image, audio).

- Knowledge of reinforcement learning and autonomous agents.

- Contributions to open-source AI/ML projects.