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Build and deploy AI models, LLMs, and NLP tools to enhance customer interactions and workflows at a customer-experience AI platform.
Build and deploy Python-based data pipelines and ML models for financial services, using Spark, TensorFlow, and SQL to analyze risk and support decision-making.
Lead AI product initiatives for Edge devices, optimizing ML models for petabyte-scale sensor and video data to improve physical operations like safety and efficiency.
Build and deploy ML models to improve job-matching for Indeed’s users, using Python, TensorFlow/PyTorch, and cloud platforms.
Build and maintain the data pipelines and tooling that feed AI/ML services for a cloud-based healthcare platform, enabling model development, deployment, and monitoring at scale.
Lead firmware design for edge AI accelerators, optimizing memory, DMA, and power while co-designing hardware specs and guiding customers on deploying PyTorch/TensorFlow models on custom silicon.
Build and maintain ML pipelines to optimize marketing campaigns using Python, PyTorch, or TensorFlow in a remote role.
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.
Design and build cloud-native AI agents and ML systems for Autodesk’s PDM/PLM workflows, focusing on LLM, RAG, MCP, and agentic architectures in production.
Build and maintain scalable Java/Python microservices and integrate ML models for an international institution using REST APIs and cloud infrastructure.
Build and maintain Python-based banking backend services and ML/AI pipelines, integrating with financial systems and ensuring regulatory compliance.
Build and maintain scalable Java/Python microservices and integrate ML models for a European institution, using REST APIs and cloud practices.
Builds and maintains Python-based backend services and ML/AI data pipelines for a banking product, ensuring regulatory compliance.
Build and deploy AI/ML models in Python for HR software, integrating them with backend systems using Django and Kubernetes.
Principal consultant advising enterprises on Generative AI, Agentic AI, and ML transformations on AWS, leading large-scale implementations and shaping cloud strategies for industries like FSI, telecom, and retail.
Integrates AI/ML components into manufacturing applications using Azure cloud services, SQL databases, and microservices architecture.
Build AI/ML-powered features for ClickHouse Cloud, integrating inference APIs and user interfaces to help users extract value from data using TypeScript and React.
Build and deploy NLP models and GenAI features for a legal AI platform, maintaining production systems and collaborating with cross-functional teams.
Build and optimize large-scale AI/ML systems for Google Cloud, leveraging distributed computing and advanced algorithms to power services like Search and YouTube.
Build and maintain ML benchmarks and evaluation tools to assess model performance and guide improvements.
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