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The MLOps/Cloud Deployment Engineer will manage the production infrastructure, CI/CD pipelines, and observability for AI and agentic systems in a regulated environment. This role focuses on cloud-native platform engineering, model governance, and performance optimization rather than model development.
Build and optimize distributed ML training/inference systems for ByteDance’s AI platforms, focusing on scheduling, resource allocation, and model deployment across heterogeneous hardware.
About Elemynt ELEMYNT is an early-stage startup built by Xora Innovation. We develop applied intelligence that brings AI into the real world. Our platform combines advanced machine learning, high-performance…
DevOps AI role focused on designing and maintaining cloud infrastructures, CI/CD pipelines, and MLOps environments for AI solution deployment in production, working within an agile team alongside AI developers and data scientists.
Build ML infrastructure—training pipelines, model registries, and deployment systems—for XYZ Reality's Construction Intelligence platform, using Python, PyTorch, Docker, and Kubernetes to take AI models from research into production on wearable AR devices.
Senior Software Engineer building scalable AI-powered backend and front-end systems that extract insights from unstructured engineering documents (CAD/BIM, technical reports). Core stack: Python (FastAPI/Flask/Django), React/TypeScript, LLM/RAG integration, vector databases, and multi-cloud deployment.
Senior Software Engineer building scalable cloud, Big Data, and ML infrastructure for AI-driven Workforce Management capabilities on AWS using Python/Java/Scala, Spark, and distributed data pipeline tools.
Build and maintain full-stack marketplace features and ML Ops infrastructure to match renters with homes, using Ruby/JavaScript/Go/Python and tools like Vertex AI and Chalk.
Senior ML Engineer designing scalable AI platforms, defining governance frameworks, and leading cross-team ML strategy to deploy safe, high-impact models at Creai, a data-driven AI startup.
Designs and maintains high-performance infrastructure for large-scale generative AI and machine learning workloads, including distributed systems, GPU compute, and MLOps pipelines in a financial firm.
The Machine Learning Engineer will design, develop, and deploy scalable ML models for Capital Markets applications using Python, PySpark, and various ML frameworks. The role involves managing the full ML lifecycle, including pipeline development, model optimization, and production integration.
The GCP Data & AI/MLOps Engineer will design and maintain secure, scalable data pipelines and machine learning workflows on Google Cloud Platform. The role involves implementing MLOps practices, automating cloud deployments, and developing web applications to support mission-critical AI and data solutions.
Build GCP data pipelines using Dataflow and Apache Beam Deliver MLOps, Kubeflow and AI/ML platform solutions Develop Python, Django, REST APIs and CI/CD automation Build GCP data pipelines using Dataflow and Apache…
Staff Software Engineer on Google's Gen AI Blackbelt Team, acting as a Generative AI subject matter expert working with Product Development and Technical Sales to bring Google Cloud AI products to customers and partners, including designing architectures and building AI-powered applications.
The Associate Director of Platform Engineering will lead the team managing hybrid compute infrastructure, developer platforms, and scientific compute environments for drug discovery. The role involves setting architectural strategy for Kubernetes-based clusters and MLOps pipelines while collaborating with data science and engineering teams.
Grow with us Are you detail-oriented with experience in software, appliances, or system engineering? Are you passionate about designing and operating cloud-native production services at scale? Do you enjoy…
Builds AI-driven data products and scalable pipelines using Cloud Build, Docker, and Kubeflow with GPU acceleration for domain insights.
Design and build advanced AI/ML solutions for Cisco’s supply chain, focusing on predictive analytics, LLMs, and agentic workflows to optimize product lifecycle and operational efficiency.
Lead Data Scientist designing and deploying ML, NLP, and GenAI models (including RAG systems) using Python, cloud platforms (Azure preferred), and frameworks like TensorFlow, PyTorch, and LangChain for an executive search firm's Digital-IT team.
Builds full-stack software for national security missions, blending algorithm development, legacy system support, and web apps using Python, Go, React, and Kubernetes. Focuses on mission-critical systems with AI/ML integration.
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