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Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the…
NVIDIA is looking for outstanding Software Engineer Interns to help develop groundbreaking technologies for AI and deep learning kernel libraries. Our team builds core software that accelerates high-impact AI workloads…
Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate Job Description & Summary At PwC, our people in data and analytics engineering focus on…
Overview Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at…
About SK hynix America: At SK hynix America, we are at the forefront of semiconductor innovation. As a global leader in HBM, DRAM, and NAND flash technologies, we develop the advanced memory solutions powering…
Designs and optimizes large-scale AI inference systems for SpaceX’s mission-critical applications, focusing on distributed infrastructure, low-latency model serving, and GPU-level optimizations to accelerate internal AI workloads.
Cohere is hiring a Backend Engineer to optimize model inference systems: building low-latency serving infrastructure, implementing batching strategies, and developing backend services behind the enterprise API. Core stack includes Go/Rust/C++, gRPC, and inference tooling like vLLM or TensorRT-LLM.
Founding ML engineer owning the AI core of wearable smart glasses for industrial field workers: building multimodal vision-language agents, real-time voice/video interfaces, eval and fine-tuning loops, and edge inference. Stack centers on Python, PyTorch, vLLM, and Triton; fully on-site in San Francisco.
Integrates open-source AI models (LLMs, embeddings, rerankers, speech) into business-critical on-prem production services at a Swiss telecom, owning solutions end to end: design, deployment, RAG pipelines, self-hosted inference stacks (vLLM, Ollama), GPU tuning, monitoring, and a 24/7 on-call rotation, using Linux, Kubernetes, and SQL.
Parasail is hiring an Engineering Site Lead to build and lead its European engineering team, staying hands-on with architecture and code while scaling the Kubernetes infrastructure, reliability, and incident response behind its global GPU-powered inference cloud for open-weight AI models.
Hands-on Forward Deployed Engineer building POCs, MVPs, and production LLM/generative-AI systems directly with AI-native customers, spanning engineering, product, and customer delivery. Core stack: Python, LLMs and open-source models, inference infrastructure (vLLM, Kubernetes, AWS/Azure/GCP).
A hands-on forward-deployed engineer at an AI inference platform who works directly with AI-native customers to turn LLM/generative AI challenges into production systems — building POCs, MVPs, and integrations in Python and deploying workloads with tools like vLLM, Kubernetes, and cloud AI platforms.
ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies…
A hands-on Forward Deployed Engineer who works directly with AI-native customers to design, build, and deploy POCs, MVPs, and production LLM/generative AI applications on the company's AI infrastructure platform, while contributing code back to the product. Core stack: Python, LLMs/open-source models, inference tooling (vLLM, SGLang, TensorRT-LLM), Kubernetes, and major clouds.
Hands-on Forward Deployed Engineer building POCs, MVPs, and production LLM/generative-AI systems directly with AI-native customers on an AI infrastructure platform. Day to day: writing Python, deploying and optimizing LLM inference workloads (vLLM, Kubernetes, cloud AI platforms), troubleshooting, and advising technical and executive stakeholders.
Разработка и внедрение LLM-агентов для преобразования истории операций в интерактивную, натурально-языковую аналитику с автоматическими тегами и персонализированными инсайтами. Используются GigaChat, Finetuning, RAG-системы и классическое ML для анализа транзакций.
Senior DevOps engineer at Akvelon extending a Kubernetes-based ML inference benchmarking framework: automating performance, latency, and scale-out benchmarking across clouds, building dashboards/reporting, and maintaining CI/CD. Core stack: Python, Kubernetes/GKE, GCP, vLLM, HPA, and GitHub Actions.
Backend owner for Rezo.ai's speech team: build large-scale audio data pipelines, real-time low-latency inference services (streaming, mid-utterance interruption), GPU training infrastructure, and integrate speech services into the existing Java platform and telephony stack. Core stack: Java, Python, Docker/Kubernetes, cloud, streaming APIs.
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