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About the Role Sanas is bringing real-time speech and language models on-premise — deployed at scale directly inside sovereign data centers, not served from behind a hosted cloud endpoint. It's one of the most…
Build and run Absa’s multi-cloud AI platform, deploying and scaling services on AWS Bedrock, Databricks, Azure AI Foundry, Hugging Face, and Kubernetes to power enterprise AI use cases across the bank.
Design and run Absa’s multi-cloud AI platform (AWS Bedrock, Databricks, Azure AI Foundry) that powers 43 live AI projects across ten African countries, focusing on FinOps, zero-trust security, and agentic AI infrastructure.
Optimize AI training and inference workloads for speed, cost, and efficiency across the full stack, from GPU kernels to distributed systems, using Python, C++, and profiling tools.
At River AI, our mission is to create personal AI owned and shaped by each individual. To achieve this, we are rewriting the entire stack from scratch: personal hardware for local inference, custom training…
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major…
Build and deploy LLM-powered tools, RAG systems, and agentic workflows, then run the Kubernetes-based AI infrastructure that serves them reliably across the company.
Build benchmarking, forecasting, and data-analysis systems for Apple’s AI inference platform to optimize performance and capacity at massive scale.
Principal engineer optimizing AI/ML compilers and runtime for AMD GPUs, focusing on MLIR/LLVM transformations and ONNX operators to accelerate training and inference workloads.
Principal ML Engineer at Grab’s AI Platform team, building and scaling ML infrastructure for Southeast Asia’s superapp, including LLM training/serving, fraud detection, and search ranking.
Build and optimize scalable training and inference infrastructure for reinforcement-learning AI agents, deploying across cloud and edge with a focus on latency, throughput, and cost efficiency.
Build and optimize low-latency, high-throughput ML inference services for CTR/CVR prediction and generative recommendation using LLMs, focusing on GPU acceleration and end-to-end pipeline optimization.
Designs, deploys, and manages Azure cloud infrastructure, including AKS clusters, databases, and CI/CD pipelines using Azure DevOps and Terraform.
Design and maintain Azure cloud infrastructure, AKS clusters, and CI/CD pipelines while automating deployments with Terraform and scripting.
Build and run the infrastructure for Generative AI products: pipelines, platforms, and security controls on AWS, including GPU clusters, model serving, and CI/CD.
Build and maintain AI infrastructure for model hosting, training, and serving at scale using Kubernetes, cloud platforms, and GPU orchestration.
Senior DevOps ML Engineer builds and runs AI platforms, splitting time between GPU-accelerated Kubernetes, backend services, and MLOps to productionize LLMs and digital avatars.
Builds and deploys production-grade AI, ML, generative AI, and computer vision systems for a hospital, integrating with EHR, imaging, and clinical workflows while ensuring safety and scalability.
Build and operate sovereign AI infrastructure for government clients, deploying GPU clusters in air-gapped data centers and cloud (Azure/GCP) using Kubernetes, GitOps, and offline artifact pipelines.
Backend engineer at a GenAI startup building scalable Go/Python systems for AI-powered avatar and video generation, serving millions of creators.
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