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Lead verification of high-speed DSP pipelines for Google’s TPU AI accelerators, ensuring pre-silicon models match physical silicon behavior using SystemVerilog/UVM and emulation.
Senior ML Engineer to research and build AI models for physical systems like robots, combining reinforcement learning, multimodal models, and real-world robotics in a collaborative research environment.
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.
Builds and scales backend infrastructure for AI-driven recommendation systems and LLM serving platforms in a fintech company.
Build and optimize production-grade LLM systems, integrating commercial APIs and self-hosted models, and implementing RAG pipelines and end-to-end LLM workflows.
Build and deploy production-grade LLM chatbots and RAG pipelines using commercial APIs and self-hosted open-source models, optimizing for latency, cost, and reliability.
Lead training, alignment, and optimization of large language models using RLHF, SFT, and quantization; build reward models, red-team models, and optimize inference pipelines in Python/C++/Rust.
Senior AI Engineer builds and deploys production-grade LLM-powered systems, agentic workflows, and real-time chat services using Python, GPU infrastructure, and Azure AI.
Build and optimize large language models for healthcare applications using fine-tuning, RAG pipelines, and production deployment in a collaborative AI team.
Design and deploy AI-powered edge-to-cloud solutions for smart cities and industrial IoT, advising customers on architecture, AI model optimization, and scalable cloud-native systems.
Builds and deploys production-grade AI, ML, generative AI, and computer vision systems for a hospital, integrating with EHR, imaging, and clinical workflows while ensuring safety and scalability.
Design and deploy end-to-end AI systems spanning edge devices, cloud, and IoT for smart cities and industrial use cases, advising customers on architecture and optimization.
Lead end-to-end training of large language models using domain-adaptive pretraining, fine-tuning, and reinforcement learning, while building robust data and evaluation pipelines for intelligent agent systems.
Builds React web apps and native iOS apps in Swift with ARKit/LiDAR for AI-powered utility-asset management; backend in Python on Azure/AWS.
Build and deploy AI models using Python, PyTorch/TensorFlow, and frameworks like LangChain and LlamaIndex; package models for production and collaborate on R&D.
Build and improve natural-language applications using Python, ML algorithms, and neural networks; analyze data and customer needs to deliver AI-driven solutions.
Build, optimize, and integrate AI models (CV/NLP) into banking systems using Python, TensorFlow/PyTorch, and MLOps pipelines.
Build and evaluate open-weight AI models for Canada’s sovereign stack: quantization evals, dataset pipelines, and inference benchmarks in a hybrid Victoria office.
Build and deploy real-time computer-vision models for a neural-interface medical device that translates brain intent into action, optimizing models for wearable hardware and clinical readiness.
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