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Build and optimize the production systems that serve Dialpad’s AI models at scale, focusing on low-latency inference, GPU utilization, and reliable deployment on NVIDIA GPUs in GCP.
Senior Forward Deployed Software Engineer on ServiceNow's Applied AI team, building and deploying production LLM-powered applications end-to-end for strategic enterprise customers in London, spanning backend services, orchestration pipelines, and front-end integrations.
Build and scale ML-driven dispute optimization systems, including training, deploying, and monitoring models, plus real-time data pipelines and feature stores for Checkout.com’s fintech platform.
Designs and builds production-grade AI agents for enterprise revenue workflows, combining deep ML expertise with hands-on agent architecture, reasoning loops, and guardrails in a hybrid Bangalore role.
Build and maintain scalable MLOps infrastructure on AWS to automate ML model training, deployment, and monitoring for a B2B sales-intelligence platform.
LSports is a world-leading sports data provider, trusted by sportsbooks worldwide to deliver real-time data with unmatched accuracy and reliability. With technology that drives smarter trading and deeper engagement, we…
Обязанности: Готовить LLM и другие генеративные модели к промышленному запуску; Выбирать inference-движок с учетом архитектуры модели, оборудования и требований продукта; Создавать воспроизводимые контейнерные образы и…
Build and operate large language model serving infrastructure at scale using Python, Kubernetes, and cloud platforms, applying site reliability engineering practices to AI platforms at J.P. Morgan.
Задачи: Создание моделей нейронных сетей в задачах Object detection, Instance Segmentation, Classification, Pose Estimation. Проработка сценариев тестирования моделей машинного обучения. Участие в создании инструкций…
Проектировать и развивать AI Gateway: единый доступ к внешним и внутренним LLM, маршрутизация запросов, лимиты, фоллбэки, контроль стоимости, аутентификация и ролевая модель доступа Развивать платформу LLM-инференса:…
Research and train large-scale diffusion models for image and video generation, ablate architectural choices, and fine-tune models for specialized tasks like upscaling and inpainting.
Привет! Это команда Возвраты ML. Мы ищем талантливого Data Scientist/ML Engineer в новую ML-команду отдела «Возвраты маркетплейса». Отдел занимается обработкой и модерацией возвратов покупателя и продавца, аннуляциями,…
The GPU Software Engineer will design and optimize high-performance CUDA kernels for AI and scientific computing workloads. The role involves profiling GPU code, collaborating with ML teams to improve training and inference pipelines, and working with modern accelerator hardware.
The Platform Engineer will develop and maintain Computer Vision services, APIs, and CI/CD pipelines while managing deployment, monitoring, and infrastructure support. The role focuses on Python-based service development and operational diagnostics for production environments.
Duties and Responsibilities: Develop and maintain Computer Vision services, APIs, configuration and error handling. Package services and models for controlled deployment, versioning and rollback. Build and maintain…
About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack…
Build and optimize distributed deep learning pipelines for large-scale genomic data in a cloud environment, collaborating with ML scientists and software engineers to accelerate cancer early-detection models.
GalaxEye is seeking a backend engineer to build and maintain ML platforms that process satellite imagery in air-gapped, offline environments. You will design data pipelines and deploy self-hosted ML models to provide geospatial intelligence for defense and intelligence applications.
Ключевые задачи: Разбирать запросы заказчиков и предлагать, каким классом решений их закрывать; Разрабатывать и улучшать RAG-пайплайны: поиск, реранжирование, сборка контекста, цитирование; Поднимать и оптимизировать…
Build and optimize framework support (Triton, PyTorch) for Graphcore's AI accelerators, working across a complex ML software stack using Python and C++.
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