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Develop and maintain production ML/computer vision systems that sort thousands of batteries per hour using PyTorch and OpenCV, integrating with factory hardware while monitoring model performance and collaborating across engineering and manufacturing teams.
Staff ML engineer at Nebius Token Factory owning LLM inference optimization end to end: turning model artifacts into fast, reliable, cost-efficient serving endpoints. Day-to-day work spans quantization, speculative decoding, KV-cache tuning, benchmarking harnesses, and engines like vLLM, SGLang, and TensorRT-LLM, built in Python/PyTorch.
Кого мы ищем Ищем Middle / Middle+ Computer Vision engineer, который умеет не просто строить модели, а делать их работающими в реальных условиях: на edge‑устройствах, в режиме реального времени, с ограниченными…
Design, build, and optimize production-grade AI systems, specifically LLM-based agentic workflows on NVIDIA GPUs, using Python and modern frameworks.
An engineer/researcher role focused on optimizing LLM inference on modern GPUs: developing and tuning CUDA kernels, analyzing GPU memory and execution bottlenecks, and benchmarking latency and throughput with frameworks like vLLM, SGLang, and TensorRT-LLM. Deep CUDA/GPU programming and low-level performance debugging skills are central to the day-to-day work.
Hands-on engineering manager at Deloitte's NVIDIA-partnered AI team, leading AI software engineers to design, build, and deliver LLM/multimodal agentic systems optimized for NVIDIA GPUs. Combines people and project management, hands-on Python coding and architecture, and client-facing technical leadership.
Обязанности: проектирование и внедрение ИИ-агентов, а также многоэтапных конвейеров обработки данных; определение оптимального стека моделей для каждого этапа обработки; обеспечение сквозного сохранения состояния…
AI Engineer at Motive in Bangalore works across the full ML stack: training and evaluating perception models for visual, audio, and fleet sensor data, then deploying them to production across edge and cloud. Core stack includes Python, PyTorch, a systems language (C++/Go), on-device ML runtimes, and distributed training/evaluation systems.
Develop and deploy machine learning solutions for computer vision and robotics applications. You will manage the end-to-end ML lifecycle, research deep learning advancements, and optimize internal AI frameworks using Python, C++, and PyTorch to solve real-world automation challenges like precision-handling and inspection.
"1、跟踪 MiniCPM、Qwen、Gemma、Phi 等小模型路线，做模型结构选型与端侧部署成本评估。 2、研究端侧多模态：图像 / 视频 / 语音 / 传感器与文本融合、视觉 token、动态分辨率、OCR、设备状态理解。 3、做后训练与任务对齐：SFT、偏好优化、拒答与安全策略、工具调用能力训练 4、用大模型蒸馏与数据合成，把云端能力压进小模型。 5、做量化与推理优化：GGUF / AWQ / GPTQ、INT4 /…
At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation…
We’re looking for a Staff/Senior Software Engineer to technically lead and build Runware’s serverless platform. You’ll be part of a small team working closely with senior leadership to bring a new product line to…
Project description Designing, optimizing, and productizing high-performance computer vision and AI pipelines for consumer device - with focus on real-time performance, power efficiency, and production robustness…
AI Engineer at CareCam who designs and trains 2D/3D computer vision models behind the 3DGait clinical gait-analysis product, builds SLM-based RAG pipelines for constrained clinical hardware, and supports testing, validation, and SaMD regulatory documentation. Core stack: Python, PyTorch/TensorFlow, RAG, edge deployment (ONNX/TensorRT), AWS/GCP.
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next…
Own Ailytics' generative AI capability end to end: fine-tune and adapt LLMs, VLMs and vision foundation models, design new features and architecture, and take models to production (including edge) on a large proprietary industrial video-safety dataset. Core stack: Python, PyTorch, Hugging Face, vLLM/SGLang.
Owns scaling PolarGrid's distributed GPU inference network: bringing new sites and nodes online, running the global request-routing layer, and hitting availability targets. Heavy focus on bare-metal GPU fleets, LLM inference engines (vLLM, SGLang, TensorRT-LLM), networking (BGP, DNS, InfiniBand), observability, and Go/Rust automation tooling.
Lead Computer Vision Engineer owning counter-UAS detection end to end at a defense-tech startup: setting technical direction for detecting, classifying and tracking drones and other aerial objects, from data curation and research through production CV models (PyTorch, OpenCV, real-time video) deployed in the cloud and on NVIDIA Jetson edge devices.
Firmus is hiring an AI Engineer focused on inference at its Sydney (The Rocks) office. The role centers on AI inference within the company's 'AI Factory' infrastructure — Firmus designs, builds, and operates efficient AI infrastructure across Asia Pacific using a model-to-grid approach with a sustainability focus.
Senior ML Engineer builds and optimizes high-performance inference engines for autonomous vehicle ML models, balancing real-time onboard constraints with offboard data center demands using frameworks like JAX, XLA, and CUDA.
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