AI-ML Architect/Lead

Key Responsibilities:

• Design and develop comprehensive architectural solutions for diverse AI and ML projects, with a primary emphasis on generative AI applications
• Create scalable and robust cloud-based AI infrastructure utilizing platforms like AWS, Google Cloud, and AWS Bedrock
• Lead the technical design and implementation of AI/ML solutions, ensuring optimal performance, scalability, and efficiency
• Evaluate, select, and integrate appropriate Large Language Models (LLMs) and generative AI technologies for specific project requirements
• Develop and maintain best practices for AI solution architecture, including model selection, fine-tuning, and deployment strategies
• Collaborate with cross-functional teams to translate business requirements into technical AI solutions
• Conduct technical assessments and provide strategic recommendations for AI technology adoption
• Guide a team of AI engineers on day to day development across projects.
• Prototype and validate AI/ML solutions, demonstrating proof of concept and technical feasibility
• Stay current with emerging AI technologies, research, and industry trends

Technical Skills

• Extensive hands-on experience with AI/ML technologies and generative AI solutions
• Profound understanding of machine learning algorithms, neural network architectures, and AI model development
• Advanced proficiency in cloud platforms, specifically: AWS (AWS Bedrock, SageMaker), Google Cloud AI Platform, Azure AI Services
• Expert-level programming skills in Python, with strong capabilities in: TensorFlow, PyTorch, Hugging Face Transformers etc, Java or C++
• Comprehensive experience with Large Language Models (LLMs) such as: ChatGPT, Claude, Llama, BERT etc
• Experience with vector databases and tools for RAG architecture (e.g., Pinecone, Weaviate, or similar).
• Advanced knowledge of MLOps and AI deployment strategies
• Experience with multimodal AI models
• Expertise in speech and voice AI technologies, including: Natural language processing for speech interfaces, Voice recognition and authentication systems, Speech-to-text and text-to-speech technologies
• Experience with model optimization and efficient AI deployment techniques
• Understanding of prompt engineering and AI interaction design
• Experience with containerization and orchestration (Docker, Kubernetes)
• Proficiency in version control systems (Git)

Qualification and Professional Experience:

• Bachelor's or masters degree in computer science, Engineering, Mathematics, Statistics, or a related field.
• Minimum 5-11 years of professional experience in AI/ML architecture and development
• Proven track record of successfully delivering complex AI/ML projects for various clients over the last few years.
• Demonstrated ability to work across multiple AI/ML frameworks and technologies