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Lead Happiest Minds’ GenAI & Agentic AI practice, building Azure AI or AWS AI solutions, driving growth, pre-sales, and enterprise delivery with frameworks like LangGraph and CrewAI.
Design and deploy ML models, LLMs, and analytical pipelines to support litigation, regulatory strategy, and AI/cybersecurity advisory for Fortune 100 clients and governments.
Research and train large language models for financial applications using PyTorch, TensorFlow, and Hugging Face to optimize AI-driven fintech solutions.
Build, deploy, and monitor ML/AI models and GenAI systems using Python, TensorFlow, PyTorch, and MLOps tooling like MLflow and Kubernetes.
Build and deploy computer-vision models for ID verification and facial recognition to automate compliance and onboarding in a global fintech app.
Senior Data Scientist builds and deploys AI models—including LLMs and computer vision—to optimize oil production workflows using Python, PyTorch, and cloud GPUs.
Senior back-end engineer building scalable RegTech and compliance automation using Python/Django, ElasticSearch, and AI-driven tools to streamline maritime trade counterparty onboarding and risk assessment.
Build Python/C++ frameworks and APIs to run Vision and Generative AI models efficiently on custom AI accelerators, profiling and optimizing performance-critical code.
Build and deploy generative AI chatbots, predictive models, and analytics dashboards using Python, LLMs, and tools like Streamlit and Power BI.
Build and deploy LLM/NLP models using Hugging Face, LangChain, and cloud AI services; implement RAG pipelines and vector search for AI-driven chatbots and Q&A systems.
Build production-grade AI features like RAG pipelines and agentic workflows using Python, FastAPI, and vector stores; ship LLM-powered services end-to-end.
Design and deploy AI/ML models, including LLMs and GenAI, to solve healthcare data challenges using Python, cloud platforms, and MLOps.
Build and deploy production-grade ML models and RAG pipelines to replace rule-based systems, focusing on model quality, evaluation, and self-hosted LLM inference.
Build and deploy ML pipelines and LLM services for a healthcare AI platform that supports population health and clinical decision-making.
Build and optimize Python-based speech-to-text models using frameworks like Whisper or Wav2Vec2, deploy them via APIs, and integrate into products.
Build and deploy AI solutions for enterprise clients using cloud platforms (Azure/AWS), large language models, and MLOps pipelines in Python.
Build full-stack web apps for healthcare workflows and integrate AI models (LLMs, RAG, agents) to automate audits, billing, and clinical decision support.
Builds full-stack features for a women’s mental-health platform using React, TypeScript, AWS, and APIs, with a focus on scalable, secure, and AI-enhanced patient/clinician tools.
Build and scale AI-powered backend services in Node.js/TypeScript on AWS to power On Air’s streaming platform, integrating ML models and APIs for content optimization and recommendations.
Build and maintain .NET backend services and AI/ML features for a real-estate platform, including gRPC APIs, vector search, and LLM-powered personalization integrated with SQL Server, MongoDB, and Elasticsearch.
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