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Builds and maintains machine learning infrastructure for AB InBev’s B2B platform BEES, including training pipelines, inference services, and monitoring, using Python, PySpark, Kubernetes, and Azure cloud.
Senior Machine Learning Engineer at AB InBev Growth Group in Campinas, Brazil, building and scaling ML pipelines for the BEES B2B platform using Python, PySpark, Kubernetes, and Azure Cloud.
Build and scale ML systems for BEES, AB InBev’s B2B commerce platform, owning end-to-end pipelines from data to production inference.
Build and maintain ML platform components for a B2B e-commerce SaaS, including training pipelines, inference services, and observability, using Python, PySpark, Kubernetes, and Azure.
Orcrist Technologies is seeking an Infrastructure Engineer to design, build, and operate bare-metal server fleets and data-center networking for their high-performance data intelligence platform. The role involves hands-on hardware commissioning, automation, and supporting GPU-based inference in both on-prem and air-gapped environments.
Зарплата: до 350000 RUR (до вычета налогов) Чем предстоит заниматься: R&D и пайплайны: Проектировать архитектуру преобразования входных данных в структуру презентаций (секции, слайды, текст, визуал). GenAI и LLM:…
About the job Help make Graphcore hardware feel native inside the ML frameworks engineers use every day. As a Software Engineer in our PyTorch team, you will help build the software that connects Graphcore accelerators…
The Senior Machine Learning Engineer will build and deploy scalable ML systems into production environments using Python and TensorFlow. The role focuses on the full lifecycle of ML models, including development, deployment, monitoring, and maintenance using TFX.
Full-stack engineer in Krafton's AI Frontier division building AI-powered product features (RAG pipelines, agent orchestration, MCP integration) end-to-end while ensuring stability and scalability under large-scale traffic, using coding agents as a core development tool.
This role involves designing, training, and deploying machine learning models into production at scale for recommendation, personalization, and forecasting systems. You will own the end-to-end model lifecycle, working with technologies like PyTorch, TensorFlow, Kubernetes, and various cloud platforms to serve millions of users.
Computer Vision engineer developing and deploying CV models for Sberbank's SmartView video analytics platform (300K+ cameras), working end-to-end from data prep and model training to production monitoring, using Python, PyTorch, and Docker/Kafka microservices.
AI DevOps/MLOps Engineer building and automating CI/CD pipelines for LLM and AI model deployment on Kubernetes/OpenShift, using Jenkins, Docker, Terraform, and model serving platforms for a Singapore-based bank.
About us We are building AI systems that can reason, use tools, and complete meaningful work in the real world. Our team works across model post-training, reinforcement-learning infrastructure, large-scale training,…
ML Operations Engineer owning production ML/LLM model serving, deployment, and operations in Mercari's cloud-native environment using Kubernetes, Terraform, Python, and NVIDIA/TPU stacks (Triton, TensorRT-LLM, JAX).
Senior Solutions Architect advising academia/research on AI/ML workloads, integrating NVIDIA’s accelerated computing tools into LLM projects, and mentoring researchers to maximize impact via publications and technical adoption.
Beacon AI is seeking Cloud and ML Infrastructure Engineers to build and maintain scalable AWS infrastructure and LLM platforms for aviation systems. The role involves designing RAG pipelines, managing model inference, and ensuring secure, high-performance deployments using tools like AWS, Python, and LangChain.
Software Engineer applying Python to AI video processing challenges at a deep tech media company building XR, interactive streaming, and cloud-native media infrastructure.
Builds and scales distributed training infrastructure for large AI models, optimizing performance and reliability across thousands of GPUs using systems like Megatron-LM and SGLang.
Lead the architecture and development of Anthropic's accelerator-agnostic inference runtime, optimizing performance and reliability for Claude across GPUs, TPUs, and Trainium while mentoring engineers and driving cross-team technical alignment.
Optimize machine learning models for training and inference at a quantitative trading firm, focusing on low-level GPU, networking, and system-level performance tuning.
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