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Build and maintain LLM servers (Llama, Mistral, GPT API) and deploy AI agents that automate tasks like reminders, reports, and paperwork using vector databases and RAG pipelines.
Build and deploy generative AI apps using Python and LangChain, focusing on RAG systems, LLM orchestration, and vector databases.
Design and build enterprise-grade AI systems using RAG, agentic workflows, and cloud platforms for HR and finance domains.
Deploys and optimizes AI infrastructure for enterprise clients using NVIDIA AI Enterprise, Milvus, and high-performance storage, automating workflows and collaborating with cross-functional teams.
Design and scale real-time data pipelines for AI systems, focusing on RAG, vector databases, and semantic layers to power agentic reasoning in enterprise environments.
Build real-time data pipelines and vector databases to power AI agents, transforming enterprise logs into embeddings for RAG systems with automated quality guardrails.
Build and maintain cloud-based ELT/ETL pipelines, orchestrate Docker/Kubernetes deployments, and automate CI/CD for a global scientific intelligence team using Python, SQL, and AWS/Azure.
Design and maintain cloud-based ELT/ETL pipelines and data infrastructure to deliver research-ready datasets for a global scientific intelligence team.
Build and scale AI/ML pipelines and GenAI systems for GE HealthCare, automating model deployment, monitoring, and lifecycle management across hybrid/multi-cloud (AWS, Azure).
Build and scale face-recognition systems using PyTorch/TensorFlow, own end-to-end ML pipelines on AWS, and lead fairness analysis for biometric models in production.
Build and deploy AI/ML pipelines using Python, FastAPI, and cloud services like GCP to serve vector-based models and microservices.
Build and run the production infrastructure for Ingersoll Rand’s GenAI program, automating CI/CD, observability, and reliability for LLM-powered apps on GCP and Snowflake.
Build and operate the cloud and DevOps infrastructure that powers Ingersoll Rand’s GenAI program, focusing on GCP, Snowflake, CI/CD, and observability for LLM-based applications.
Build and operate the cloud and MLOps infrastructure that powers Ingersoll Rand’s GenAI program, focusing on GCP, Snowflake, CI/CD, and AI observability.
Build and tune LLM-based AI agents and RAG systems for ERP automation and SaaS knowledge bases, using Python, PyTorch, LangChain, and cloud pipelines.
Build LLM-based agents and RAG systems for autonomous network operations, integrating fault diagnosis, predictive analytics, and closed-loop decision support using Python, LangChain, and vector/graph databases.
Build and deploy enterprise Generative AI apps using LLMs, RAG pipelines, and AI agents with Python, LangChain, and vector databases.
Surf AI is the agentic operations platform for enterprise security teams. We don't just surface risk, we close it. Our platform connects context across identity, cloud, HR, IT, and SaaS systems, and uses…
Design and build scalable AI/ML infrastructure for a global fintech leader, focusing on real-time fraud detection and liquidity optimization using AWS, Kubernetes, and PyTorch.
Build and maintain robust data pipelines and cloud data platforms, preparing data for AI systems and ensuring quality and governance for analytics and agentic use cases.
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