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Research and develop AI models for physical robots, training vision-language-action systems and reinforcement-learning policies to perceive, reason, and act in the real world.
Research and build large-scale machine learning models for physical AI systems, focusing on robotics, reinforcement learning, and multimodal models to enable intelligent agents to interact with the real world.
Role Summary: As an Automotive Field Application Engineer, you will provide comprehensive customer-facing technical support for Automotive MCU–based applications across multiple automotive domains. This role requires…
Responsibilities: Work with worldwide design, applications and marketing teams to promot NXP MPU product. With technical expertise, to find out customer new requirement and new opportunity for NXP MPU product. Support…
Optimize LLM inference performance on Intel GPUs by profiling bottlenecks, writing custom kernels, and contributing to open-source serving frameworks like vLLM and SGLang.
Build and maintain an AI platform on Google Cloud for an insurance company, deploying GenAI/ML services, vector search, and agentic frameworks to power enterprise teams like Actuarial and Underwriting.
Build and deploy enterprise LLM applications, RAG systems, and AI agents using open-source models (DeepSeek, Qwen, Kimi) and frameworks like LangChain and vLLM.
Build and own AI-powered document processing systems: deploy open-source LLMs, design REST APIs, and integrate AI features into web apps with streaming responses and RAG pipelines.
Engineer AI/LLM inference on GPU clusters: benchmark, tune, and optimize model serving with vLLM, Triton, or TensorRT-LLM to hit latency, throughput, and memory targets.
Own and scale the reliability, performance, and cost of ManyChat's AI infrastructure, including LLM inference services and AI Gateway, while shaping standards for the company's AI platform.
WHO WE ARE 🌍 Creating content that resonates is great — turning that attention into growth is even better. That's what Manychat does. Our AI-powered automations help creators and brands engage with audiences…
Research and develop on-device generative and 3D spatial AI models for mobile platforms, optimizing models for edge deployment and shipping to product.
Build and optimize real-time graphics and ML inference pipelines for interactive visual apps, integrating super-resolution and denoising models into DX12/Vulkan renderers.
Build and deploy realtime intent-drift detection models for AI coding agents running on developer machines, using small open models and local-first Python tooling.
Leads the build-out of an internal AI and data platform to power non-engineering functions like Finance, HR, and Sales, using LLMs, agent frameworks, and modern data engineering.
Optimize and port AI inference/training kernels (SGLang, Miles) across NVIDIA/AMD GPUs, TPUs, CPUs, and emerging accelerators to maximize performance on heterogeneous hardware.
Build and optimize on-device AI inference software for NVIDIA GPUs, focusing on low-latency, memory efficiency, and deployment on RTX/DGX systems.
Build and optimize ML models to enhance Altera’s FPGA compiler, focusing on timing closure, resource utilization, and power efficiency using PyTorch/TensorFlow.
Design and deploy cutting-edge AI/ML applications, including LLMs and computer vision, in a defense-focused R&D environment requiring Secret clearance.
Develop and optimize deep learning models for autonomous truck perception, mapping, and planning using PyTorch, collaborating with cross-functional teams to integrate solutions into production pipelines.
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