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Senior IC role architecting and building production-grade ML, generative AI, and agentic AI systems (LLMs, RAG, SLMs) with MLOps practices for commercial pharma use cases in Bangalore.
The Sr. Principal Machine Learning Engineer will architect and deploy production-grade AI systems, including LLMs, RAG, and agentic workflows, to support pharmaceutical commercial and field engagement use cases. The role involves leading technical design, implementing MLOps/LLMOps practices, and mentoring teams while ensuring scalability, governance, and performance.
Job Description We are looking for multiple seasoned Senior and Staff System Engineers to grow an Edge AI & Systems software team to the next level. This team works within the larger ASIC team to architect and…
Description: Lead applied research and strategic definition of machine learning algorithms, quantization methodologies, and toolchain capabilities for the Neural Network Development Kit (NDK) roadmap targeting…
At JPMorganChase, we are building the infrastructure that powers the next generation of enterprise AI — and we need talented engineers who are passionate about LLM inference to help us do it. This is your opportunity…
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an…
Edge AI Engineer– Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic…
Are you looking for a unique opportunity to be a part of something great? Want to join a 17,000-member team that works on the technology that powers the world around us? Looking for an atmosphere of trust, empowerment,…
Join the AI Studios Engineering org within Prime Video and Amazon MGM Studios as a Machine Learning Engineer on CreativeFlux, the ML platform powering Nara, our AI-native content creation platform for professional…
The OpenSearch Vector Search team builds and operates the core vector search engine that powers recommendations, semantic search, and multi-modal search capabilities across Amazon's flagship services including…
Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in…
RDA Technologies Limited in Hong Kong seeks researchers or aspiring researchers to construct and augment large-scale communication datasets to fuel AI model training. You will rapidly reproduce state-of-the-art…
Мы строим новое AI-направление и создаем команду, которая станет центром компетенций по искусственному интеллекту и будет развивать AI-функциональность сразу в нескольких продуктах компании. Сейчас мы формируем команду…
Design and deploy AI/LLM models on FuriosaAI’s RNGD NPU using the Furiosa SDK, running POCs, benchmarks, and debugging for US customers while translating technical capabilities into business value.
This role involves creating and maintaining developer-facing documentation for FuriosaAI's SDK and LLM software stack using a docs-as-code approach. The engineer will build automated validation pipelines to ensure documentation accuracy against live hardware and code releases.
About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea…
AI Forward Deployed Engineer owning customer deployments end-to-end at Fireworks—embedding in client environments to unblock production issues around capacity, model selection, latency, and integration using Python, generative AI inference/serving, and GPU infrastructure.
Senior AI Engineer designing, building, and operating production-grade Generative AI solutions on the Microsoft Azure AI ecosystem—from model selection and RAG architecture through deployment, MLOps, security, and governance.
Own the end-to-end post-training pipeline—SFT, RL, DPO, evals, distillation, and deployment—on top of SF Tensor's custom GPU compiler and Model Foundry infrastructure, working primarily with PyTorch or JAX.
Analyze and optimize ML inference performance (latency, memory, power) on Apple Silicon, working across the SW stack, low-level drivers, and HW debug involving CPU, GPU, and Neural Engine using Python/C++ and frameworks like PyTorch and MLX.
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