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At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for…
Student engineer builds and validates CI/CD pipelines, test suites, and observability tooling for Amazon’s ML accelerator hardware and inference software stacks.
This role involves working with major Chinese Cloud Service Providers to architect and deploy NVIDIA BlueField DPU and DOCA-based networking solutions for Agentic AI workloads. The architect will lead technical engagements, optimize North-South traffic, and bridge local customer requirements with NVIDIA's global product roadmap.
Your Job The Senior LLM Engineer will fine-tune and deploy LLMs on Azure OpenAI / Azure AI Foundry to power generative AI capabilities within our engineering design platform, translating natural-language design intent…
Builds next-gen multimedia AI computing platforms for TikTok, focusing on multimodal data processing, foundation model training, and real-time AI services. Works on distributed infrastructure, GPU/CPU cluster orchestration, and cloud-native systems to scale video processing for billions of daily videos.
Senior Staff Software Engineer on LinkedIn's AI Infrastructure team, responsible for designing and optimizing large-scale distributed training and serving systems for AI models (e.g., LLMs, recommendation engines), using frameworks like PyTorch, TensorFlow, Horovod, and DeepSpeed to scale up to hundreds of billions of parameters and high-throughput GPU inference.
An AI Engineer at Tractian develops and optimizes large language model (LLM) applications and backend systems, collaborating with cross-functional teams to ensure project success and efficient deployment.
Leads ROCm software validation for AMD’s AI/ML GPU platforms, defining test strategies, infrastructure, and release gates for multi-GPU/server workloads (e.g., LLMs, HPC). Owns end-to-end validation, debugs complex failures, and mentors engineers.
Build and scale LLM inference infrastructure for enterprise AI workloads, enabling customers to serve and optimize frontier models with high reliability and performance.
Designs and builds high-scale APIs for serving large language models (LLMs) and GPU inference workloads, focusing on performance, reliability, and operational excellence.
Привет! Это команда Базовых ML Моделей. Мы строим единую систему оценки качества ML-решений в Озоне — от классических моделей до больших языковых моделей. Наша задача — находить лучшие ML-разработки внутри компании,…
At d-Matrix , we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is…
You build benchmark pipelines for LLM inference performance, create model launch gates, maintain representative workloads, compare model and runtime options, automate regression detection, and collaborate with runtime…
About Majestic Labs We’re a fast-moving, US-Israeli AI startup building next-generation infrastructure for the world’s most demanding AI workloads. Our mission is to accelerate the future of intelligence and make it…
Own the end-to-end architecture of a production serving harness for in-house vision-language models (OCR and structured extraction), optimizing accuracy, latency, and cost at national scale using Go, Python, Temporal, Kubernetes, and PostgreSQL.
Designs, codes, and deploys scalable GenAI services, chatbots, and autonomous agents using modern frameworks; maintains LLM infra on-premise (Docker/Kubernetes), optimizes RAG pipelines, and ensures security. Core tech: Python, LLMs, RAG, vector databases, Docker/Kubernetes.
A Forward Deployed Engineer (FDE) at Mentat deploys an enterprise AI platform on-premise at client sites, configures GPU clusters, integrates with customer systems, solves on-site problems, and provides feedback to improve the product, focusing on LLMs, embeddings, and containerized infrastructure.
ML engineer builds adaptive agent-based retrieval systems, fine-tuning LLMs and optimizing multi-step search strategies using SFT/RL and frameworks like ReAct.
AI Backend Engineer at 멘타트, designing and operating search, agent, and workflow backends for an enterprise AI platform using technologies like hybrid search, LLM agents, and vLLM. Core tasks include building hybrid search pipelines, LLM agent harnesses, and GPU cluster infrastructure for regulated domains (legal/financial).
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