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Build and deploy AI features for banking platforms, leading from prototype to production while ensuring regulatory compliance and cross-team adoption.
Build and deploy AI/ML systems for B2B financial operations, focusing on invoice matching, payment reconciliation, and agentic workflows using LLMs and RAG in a fintech SaaS platform.
Build and maintain the AI platform and data lakehouse, automating operations and deploying services using Python, Kubernetes, and MLOps tools.
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major…
Build and deploy LLM-powered tools, RAG systems, and agentic workflows, then run the Kubernetes-based AI infrastructure that serves them reliably across the company.
Build benchmarking, forecasting, and data-analysis systems for Apple’s AI inference platform to optimize performance and capacity at massive scale.
Build and deploy AI/ML systems for classified missions, translating user workflows into LLM-powered or agent-based automation that integrates with existing platforms.
Build and optimize Python-based backend and AI systems for a fintech startup, applying LLMs and RAG pipelines to financial data to deliver real-time insights for asset owners.
Principal ML Engineer at Grab’s AI Platform team, building and scaling ML infrastructure for Southeast Asia’s superapp, including LLM training/serving, fraud detection, and search ranking.
Build and maintain an internal AIOps/ML/LLM platform, including Kubernetes infrastructure, ML workflows, and production deployment for cybersecurity use cases.
Build and ship end-to-end AI features that turn model capabilities into reliable, real-world user workflows using Python, PyTorch/JAX, and vector DBs.
Build and scale AI-driven document systems, focusing on PDF processing, RAG pipelines, and LLM-powered retrieval/analysis for enterprise workflows.
Junior software engineer building AI-powered document applications, focusing on Python, LLMs, and PDF processing workflows.
Junior software engineer building AI-powered document applications, focusing on PDF processing and LLM-driven workflows using Python.
Build and optimize scalable training and inference infrastructure for reinforcement-learning AI agents, deploying across cloud and edge with a focus on latency, throughput, and cost efficiency.
Build and deploy scalable AI systems that turn physical-world data into enterprise intelligence, optimizing energy and operations for industries like climate tech.
Build and own the AI layer for Elderwise, fine-tuning LLMs to convert caregiver notes into clinical documentation, with embeddings, RAG, and evaluation systems for accuracy and safety in healthcare.
Lead the design and deployment of GenAI solutions for insurance, including RAG pipelines, vector databases, and LLM fine-tuning on AWS to deliver context-aware AI capabilities.
Build and optimize distributed orchestration frameworks for large-scale ML training and inference in Kubernetes, focusing on resource efficiency and next-gen recommendation systems.
Build and optimize low-latency, high-throughput ML inference services for CTR/CVR prediction and generative recommendation using LLMs, focusing on GPU acceleration and end-to-end pipeline optimization.
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