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Build AI-powered features like search, recommendations, and generative AI tools for a healthcare marketplace, spanning models, APIs, and user interfaces.
Designs and deploys end-to-end machine learning solutions for clients, bridging business problems with statistical modeling, cloud-based analytics, and production-grade MLOps. Focuses on Azure-based pipelines, model governance, and stakeholder collaboration.
Senior ML Engineer at Kensho (S&P Global) building GenAI platforms, LLM-powered agents, and AI toolkits end to end, from modeling through production deployment using Python, LLM orchestration, and cloud infrastructure.
Build and deploy production-grade ML systems, including retrieval-driven AI agents and LLM-powered applications, using Python, PyTorch, and LangChain to power Kensho’s AI toolkits and generative AI products.
Build and deploy ML models from scratch (e.g., Random Forests, Neural Networks) to detect spam and threats, using Python and cloud infrastructure without managed services.
Build and deploy scalable ML pipelines on AWS and Databricks, leading a team to integrate generative AI models and APIs for healthcare analytics.
Builds and deploys AI-driven systems (RAG, agents) for Thomson Reuters’ investigative platform CLEAR, integrating AI into full-stack web apps, APIs, and enterprise workflows for legal/tax/compliance domains.
Builds and deploys ML/AI models to analyze healthcare data, improve predictive accuracy, and automate workflows using agentic systems and RAG techniques.
Senior Data Scientist leading ML model development and deployment in a distributed data system to maximize weapon system operational effectiveness for Boeing Defense, Space & Security.
Build and optimize distributed inference support in the AWS Neuron SDK for custom ML accelerators (Inferentia/Trainium), working across the full stack from PyTorch/JAX frameworks down to hardware-specific kernels and system-level optimizations.
Lead ML strategy, model development, and a team for AquaEye's AI-powered handheld sonar devices used in water rescue, working with Python, C, PyTorch, Scikit-learn, and embedded ML on IoT hardware.
Designs AI-driven systems to monitor and optimize Disney’s global streaming ecosystem (Disney+, Hulu, ESPN) by building real-time telemetry pipelines, agentic models, and observability tools for reliability and performance.
Design and build scalable AI/ML systems at Nike, leveraging prediction models and generative AI to drive data-driven business decisions and optimize corporate functions.
Lead AI/ML Engineer at Nike owning end-to-end ML and generative AI solutions for corporate functions, from design through production, using Python, AWS (SageMaker, Lambda), and MLOps practices.
Builds AI-powered automation solutions for internal business processes (Finance, HR, Logistics) by designing agentic systems, integrating LLMs/RAG, and deploying scalable production-grade models while ensuring security, governance, and observability.
Architect, build, and scale backend services for an agentic AI platform at Adobe, designing APIs, data pipelines, and agent orchestration infrastructure using Python, LLMs, vector databases, and cloud platforms.
The Staff Data Scientist will lead the development of next-generation AI systems and autonomous agents to improve Walmart's global operations. The role involves architecting end-to-end ML pipelines, mentoring senior talent, and deploying production-grade AI solutions using technologies like PyTorch, LangChain, and cloud-based ML platforms.
The Senior Machine Learning Scientist will develop generative and representation learning models for protein and antibody drug discovery. The role involves collaborating with cross-functional teams to apply advanced ML techniques to large biological datasets.
This role involves developing real-time software and digital signal processing applications for RF systems, including embedded and distributed architectures. The engineer will work on hardware-software integration, debugging, and system-level testing while mentoring junior team members.
The Senior Machine Learning Scientist will develop generative and representation learning models for protein and antibody discovery within Roche's AI for Drug Discovery group. The role involves collaborating with cross-disciplinary teams to apply advanced ML techniques to large-scale biological datasets.
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