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Build and deploy NLP models for federal clients, focusing on text preprocessing, feature engineering, and transformer-based solutions to solve public-sector challenges.
Lead the architecture and team behind Inari’s data, AI, and engineering platform, integrating AWS, Kubernetes, and AI workflows to support predictive design and scientific computing for sustainable agriculture.
Build, deploy, and monitor ML models end-to-end using Python, scikit-learn, and cloud platforms to drive business impact in insurance and financial services.
Design and build AI-powered applications using cloud services, generative models, and deep learning pipelines in production environments.
Lead the design and delivery of scalable AI and data platforms, from petabyte-scale lakehouses to production GenAI solutions, using Python, Spark, Databricks, and cloud services.
Build and deploy enterprise-scale generative AI and LLM-powered systems for Morgan Stanley’s investment banking tech stack, focusing on RAG, agents, and MLOps in a regulated financial environment.
Build and deploy AI solutions for Amgen’s drug discovery and operations, integrating GenAI, RAG, agents, and MLOps in a regulated healthcare environment.
Build and deploy AI/ML solutions end-to-end for Amgen’s AI Studio, turning business problems into scalable GenAI, RAG, and agent-based products with MLOps and enterprise integrations.
Build and own end-to-end AI products from problem framing to production deployment, focusing on GenAI, RAG, agents, and MLOps for Amgen’s healthcare domain.
Build and own production ML/AI components for Amgen’s AI Studio, including GenAI, RAG, and retrieval systems, using Python, SQL, and cloud services.
Build and deploy production ML and GenAI components—models, RAG systems, agents, and pipelines—using Python, SQL, and cloud services to power Amgen’s healthcare-focused AI products.
Build, deploy, and monitor ML models and MLOps pipelines on AWS for forecasting and GenAI apps in a biotech setting.
Build, train, and deploy AI models (ML, DL, generative, RAG, agents, computer vision) in Python, then wrap them in APIs for production use.
Designs and deploys production-grade generative AI systems on Databricks for enterprise clients, focusing on RAG pipelines, LLM orchestration, and vector search while leading technical delivery.
Build and scale secure AWS infrastructure (EKS, Lambda, Terraform) for AI/ML workloads, automate CI/CD with GitLab, and run a centralized observability stack (Prometheus/Grafana) to support production LLM inference and vector databases.
Lead a team of ML engineers and architects at an AI-first cloud services company, owning hiring, team growth, and complex customer engagements while shaping AI/ML architectures and driving pre-sales.
Leadership and Delivery Lead project delivery end to end, with clear governance, stakeholder communication, and accountability for outcomes Build and mentor a high-performing AI engineering team, establishing technical…
Teamwork makes the stream work. Roku is changing how the world watches TV Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world.…
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