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Build and maintain scalable, reliable AI/ML platforms and infrastructure at JPMorganChase, focusing on observability, security, and cloud-native delivery in AWS/GCP/Azure.
Build and deploy AI/ML solutions for legal and enterprise clients using Python, TensorFlow/PyTorch, and cloud platforms like Azure/AWS.
Build AI/ML systems to optimize clinical trial design using GenAI, agentic frameworks, and scientific data to cut drug development time and costs.
Build and maintain ML pipelines on Azure and Databricks, deploy models, and set up MLOps processes for a higher-education group.
Build and deploy NLP/LLM models to automate customer support tasks like intent detection, chatbots, and agent routing for Zendesk’s AI-powered CX platform.
Build and deploy deep-learning models for crashworthiness, human-body modeling, and electronics drop-shock simulation using Python/C++ on Linux/Windows.
Leads AI/ML system design and deployment for global payments and trade, overseeing scalable ML pipelines and model integrations to optimize financial services.
Build and scale production-grade RAG systems for enterprise search and question answering using LLMs, vector databases, and retrieval pipelines.
Build and deploy agentic AI systems for financial data, focusing on LLM orchestration, retrieval, and scalable workflows to power research and insights.
Design and implement AI/ML models for logistics optimization, predictive analytics, and anomaly detection to support defense supply chain challenges.
Design, build, and deploy ML models and AI systems for a global talent marketplace, spanning data prep to production monitoring using Python, TensorFlow/PyTorch, and MLOps tooling.
Build and deploy production-grade ML and LLM systems across multi-cloud, designing end-to-end pipelines and MLOps workflows with PyTorch/TensorFlow and cloud-native tooling.
Build and scale production-grade RAG pipelines, retrieval systems, and LLM orchestration for enterprise search and knowledge discovery in financial data.
Build and deploy agentic AI systems for financial data, focusing on LLM orchestration, retrieval, and scalable workflows to power generative AI applications in finance.
Build and optimize AI/ML models for extracting structured data from unstructured documents using NLP, computer vision, and LLMs, and deploy scalable ML pipelines for high-volume processing.
Build and maintain AWS-based cloud infrastructure and MLOps pipelines to support AI/ML research, enabling faster model training, deployment, and experimentation for GE HealthCare’s research teams.
Develops advanced autonomy algorithms and foundation models to extract semantic meaning from real-world driving data, optimizing datasets and deploying ML models in safety-critical physical systems for Uber’s AV Labs.
ABOUT SINCH Sinch is pioneering the way the world communicates. More than 150,000 businesses — including Google, Uber, Paypal, Visa, Tinder, and many others — rely on Sinch’s Customer Communications Cloud to power…
About the Role We are looking for a Python Software Engineer to join our engineering team and work at the intersection of software development, machine learning, and embedded systems. The primary focus of this role is…
Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep…
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