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Build and deploy AI/ML models for healthcare claims processing using PyTorch/TensorFlow, MLOps pipelines, and cloud tools to reduce payment inaccuracies and waste.
Senior role defining and delivering AI/ML solutions for an auto-lending fintech, owning end-to-end product lifecycle from problem framing to launch and KPI tracking.
Lead a team to build and deploy large language model applications, fine-tune models, and create agentic AI systems for mission-critical government use cases.
Builds and deploys AI-powered applications by integrating LLMs, developing full-stack features (React/Next.js frontends, FastAPI/Flask backends), and optimizing RAG pipelines with vector databases for scalable, production-ready solutions.
Build and maintain APIs and MCP servers that expose ML models from Databricks to internal apps and AI agents, ensuring reliability, security, and scalability.
Build and deploy production-grade generative AI systems—LLMs, RAG, and AI agents—to automate document processing, customer support, and decision workflows in a regulated banking environment.
Build, document, and optimize production-grade AI/ML pipelines and model integration layers using Python, PyTorch, and vector databases.
Build and deploy production-grade generative AI systems (LLMs, RAG, AI agents) for a large bank, focusing on NLP, document intelligence, and responsible AI in a regulated environment.
Build and deploy production-ready AI-powered apps using LLMs, full-stack dev, and cloud infrastructure; optimize performance, reliability, and security.
Build and harden enterprise data products in Snowflake and dbt, using SQL and Python to deliver governed, scalable datasets for analytics, AI-enabled apps, and ML pipelines at a cybersecurity company.
Design and build enterprise-grade MLOps/LLMOps platforms on AWS SageMaker and EKS, automating model lifecycle from training to monitoring and ensuring scalable, secure AI deployments.
Build and deploy AI/ML systems for drug discovery and patient care, including GenAI, RAG, and agents, using Python, cloud platforms, and MLOps/LLMOps pipelines.
Senior Data Scientist builds and deploys ML and LLM-powered apps for healthcare clients, turning EHR, claims and clinical data into predictive models and AI workflows that improve patient outcomes and operations.
Principal Data Scientist designs and delivers healthcare AI solutions using Azure ML and Databricks, translating clinical data into production-ready models while ensuring governance and responsible AI practices.
Senior Data Engineer builds and maintains the data foundation for clinical decision-making, integrating diverse data sources and enabling AI-driven insights across drug development at a global healthcare company.
Build and deploy ML models for weather forecasting using PyTorch and HPC systems, integrating with numerical weather prediction pipelines and operational environments.
Pre-sales solution architect designs and deploys scalable AI infrastructure on Kubernetes for European enterprises using Mirantis k0rdent, guiding customers through hybrid and multi-cloud deployments.
Builds and deploys autonomous AI agent systems for government missions, focusing on agentic workflows, multi-agent collaboration, and cloud-native architectures using Python and modern AI frameworks.
Design and build the enterprise AI platform’s core architecture, reusable patterns, and agentic AI systems for New York Life’s insurance and financial services.
Build New York Life’s enterprise AI platform and agentic solutions, spanning cloud-native infrastructure, multi-agent orchestration, retrieval systems, and governance—using Python, GCP, and AI-assisted tools.
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