Machine Learning & AI Innovation Lead

As a Lead AI/ML Engineer with 6+ years of experience, your role will involve leading technical efforts in AI technologies like large language models (LLMs), computer vision, machine learning, and data science to solve high-impact business problems. You will be responsible for mentoring team members, guiding architecture decisions, and overseeing end-to-end AI solution delivery in cloud-based environments. Key Responsibilities: - Leadership & Strategy - Drive the technical vision and roadmap for AI/ML and Generative AI initiatives. - Lead and mentor a team of AI/ML engineers and data scientists, conducting regular code reviews and guiding solution architecture. - Collaborate with cross-functional stakeholders to translate business problems into scalable AI/ML solutions. - Own the AI/ML lifecyclefrom prototyping and experimentation to production deployment and monitoring. - Generative AI & LLMs - Architect and lead the development of scalable Generative AI solutions using AWS Cloud and modern frameworks. - Expertise in working with large language models (LLMs) including fine-tuning, evaluation, and deployment. - Proficient with GenAI frameworks like Langchain, Langgraph, Langfuse, Crew AI, and others. - Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise applications. - Machine Learning & Data Science - Solve complex machine learning problems using various methods. - Lead the implementation of ML pipelines including automated data preprocessing, training, validation, and monitoring. - Manage ML lifecycle using AWS SageMaker, including model versioning, drift detection, and retraining strategies. - Apply advanced analytics, time series forecasting, and predictive modeling techniques. - Computer Vision - Design and deploy advanced computer vision models for classification, object detection, segmentation, and image captioning. Skills & Qualifications: - 6+ years of experience in AI/ML, with at least 3 years in Generative AI and LLMs. - Strong proficiency in Python and ML libraries such as Scikit-learn, XGBoost, LightGBM, CatBoost. - Deep understanding of LLMs including OpenAI (GPT-4, GPT-4o), Claude, Gemini, LLaMa, DeepSeek, etc. - Proficiency with GenAI tooling: Langchain, Langfuse, Crew AI, LLAMA Index, Langgraph, etc. - Experience with deep learning frameworks like PyTorch and TensorFlow. - Strong experience with AWS services: SageMaker, Bedrock, DynamoDB, S3, Lambda, etc. - Proficiency in REST API development using FastAPI, Uvicorn, Flask, Docker, and related tools. - Strong database knowledgeboth SQL (PostgreSQL) and NoSQL (DynamoDB). - Familiarity with caching systems like Redis and Memcached. - Strong communication skills and ability to lead discussions with technical and non-technical stakeholders. Preferred: - Experience in leading enterprise-scale AI/ML deployments. - Contributions to open-source GenAI/ML projects. - Certifications in AWS AI/ML or equivalent. As a Lead AI/ML Engineer with 6+ years of experience, your role will involve leading technical efforts in AI technologies like large language models (LLMs), computer vision, machine learning, and data science to solve high-impact business problems. You will be responsible for mentoring team members, guiding architecture decisions, and overseeing end-to-end AI solution delivery in cloud-based environments. Key Responsibilities: - Leadership & Strategy - Drive the technical vision and roadmap for AI/ML and Generative AI initiatives. - Lead and mentor a team of AI/ML engineers and data scientists, conducting regular code reviews and guiding solution architecture. - Collaborate with cross-functional stakeholders to translate business problems into scalable AI/ML solutions. - Own the AI/ML lifecyclefrom prototyping and experimentation to production deployment and monitoring. - Generative AI & LLMs - Architect and lead the development of scalable Generative AI solutions using AWS Cloud and modern frameworks. - Expertise in working with large language models (LLMs) including fine-tuning, evaluation, and deployment. - Proficient with GenAI frameworks like Langchain, Langgraph, Langfuse, Crew AI, and others. - Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise applications. - Machine Learning & Data Science - Solve complex machine learning problems using various methods. - Lead the implementation of ML pipelines including automated data preprocessing, training, validation, and monitoring. - Manage ML lifecycle using AWS SageMaker, including model versioning, drift detection, and retraining strategies. - Apply advanced analytics, time series forecasting, and predictive modeling techniques. - Computer Vision - Design and deploy advanced computer vision models for classification, object detection, segmentation, and image captioning. Skills & Qualifications: - 6+ years of experienc