Job
Description
Responsibilities: Customer & Architecture Interact with customers to define problem statements and technical requirements Design and architect AI/ML cloud solutions using AWS/GCP Create system architecture diagrams and establish best practices for ML systems Define data architecture and model serving strategies Technical Leadership & Development Guide team in building Python-based APIs and AI/ML models Design and implement ML pipeline automation Establish model deployment and monitoring architectures Review technical designs and approve implementation approaches Lead architectural decision-making and technical direction Project & Team Management Overall responsibility for project/program delivery Manage and mentor AI/ML engineers Lead sprint planning and technical grooming sessions Coordinate with cross-functional teams Balance resource allocation and technical debt Qualifications Must have at least 10 years of IT experience with 5+ years experience in designing, developing, deploying, and operationalizing AI/ML solutions. Experience in GenAI and Conversational AI LLMs, frameworks like Lang chain, Llama Index etc, Vector DBs like Pinecone, Elasticsearch, etc. Deep understanding and experience with popular Deep Learning and Machine Learning techniques and algorithms such as LLMs, Neural Networks, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), LSTM, Transformers, Time Series Forecasting, Segmentation, etc. Experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps/LLMOps, Optimization techniques, and AI solution Architecture. Experience with ML Pipelines both On-Prem and Cloud (like SageMaker) Expert in Python as well as open-source frameworks such as PyTorch, TensorFlow, NumPy, etc. Experience in designing cloud-native solutions using AI and other services from Azure, GCP, AWS, etc. Ability to lead Data Engineers and ML engineers to provide guidance on technical architecture and best practices.
