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Training Operations Manager | 2:00 PM–10:00 PM For our client, an international organization, we are looking for an experienced Training Operations Manager to join a newly developing global Training Operations team.…
Design, implement, and operate the network infrastructure for GovTech Singapore's on-premises private cloud across multiple government data centres, using spine-leaf topologies with eBGP, EVPN, VRFs, OpenShift networking, and automation via Ansible, Python, and IaC. Also drives SRE practices: observability, runbooks, on-call, and incident response.
Monee, a Southeast Asian digital payments and financial services company under Sea Limited, seeks a machine learning engineer in Singapore to build graph deep learning models (GAT/RGAT via PyTorch, DGL/PyG) over large-scale user relationship and transaction data to improve credit risk scoring, covering graph construction, training, evaluation, and production deployment.
Deep Learning Engineer at Monee (Sea Limited's digital payments/fintech arm) building next-generation credit risk models in Singapore — replacing tree-based pipelines with deep learning, large-scale pre-trained models, and reinforcement learning for credit limit and pricing decisions. Core stack: Python, PyTorch/TensorFlow/JAX.
The AI Platform & Machine Learning Engineer will build and maintain scalable infrastructure for training, deploying, and monitoring machine learning models for wearable construction technology. The role focuses on the end-to-end ML lifecycle, utilizing tools like Python, PyTorch, and containerization to bridge the gap between research and production.
Tether is hiring a 100% remote AI Research Engineer to advance multi-modal reinforcement learning — building RL infrastructure, reward models, simulation environments, and training frameworks spanning text, image, and audio, using PyTorch, with the goal of publishing at top-tier ML conferences.
Tether is hiring a fully remote AI research engineer to post-train large language models for agentic behavior — tool use, function calling, reasoning, and multi-agent coordination, including on edge devices. Day to day: designing post-training algorithms, curating agentic training data, and building distributed training and evaluation/benchmark infrastructure.
AI Research Engineer on Tether's AI model team (Tether Data), driving end-to-end development of vision-language models: curating multimodal datasets, running post-training (SFT, distillation, RLHF), building evaluation benchmarks, and optimizing models for deployment on distributed GPU infrastructure.
Research engineer on Tether's AI team running large-scale pre-training of LLM and multi-modal (text/vision/audio) models on distributed clusters with thousands of NVIDIA GPUs. Day to day: designing architectures and tokenizers, curating massive datasets, running experiments, and debugging training bottlenecks using PyTorch and Hugging Face.
Amida Technology Solutions is a DC-based technology company focused on data interoperability, integrity, governance, and security. We create solutions that collect, reconcile, transform, and standardize data for…
Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. Vantor is a place for problem solvers, changemakers, and…
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping…
About Marvell Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative…
Develops, fine-tunes, and deploys production NLP/LLM models using transformer architectures with PyTorch or TensorFlow, serving them via FastAPI-style REST APIs and monitoring them in production. Familiarity with agentic AI frameworks (LangChain, LangGraph) and Docker/Kubernetes deployment is emphasized.
About the Role & Mission AI infrastructure is undergoing a generational shift. Disaggregated, raw GPU hardware must be transformed into multi-tenant, production-ready, and sovereign AI clouds - without locking…
Senior individual contributor at Cognitiv (an AdTech/deep-learning advertising platform company) who designs low-latency, high-throughput feature pipelines and optimizes large-scale ad model training pipelines for real-time bidding. Core stack: Python/Java/Scala, Spark, Flink, Kafka, PyTorch, Kubernetes, AWS, plus LLM/embedding integration.
A Principal Technical Product Manager at Cotality (formerly CoreLogic) who defines and owns the roadmap for enterprise AI platforms, bridging AI research, engineering, and data teams to ship production-grade systems. Work centers on the modern AI stack (vector DBs, LangChain/LlamaIndex, vLLM, Hugging Face, Triton) on cloud-native infrastructure like Kubernetes and GPU orchestration.
Builds and maintains the ML platform — tooling, frameworks, dataset generation, cloud training and evaluation pipelines — so ML engineers can iterate on and ship Perception, Prediction and Planning models for Toyota's AD/ADAS stack deployed in millions of vehicles. Core stack: Python, PyTorch/TensorFlow, Docker/CI, cloud infra; hybrid with 3 days/week in the Nihonbashi, Japan office.
Builds and maintains the ML platform behind Toyota's AD/ADAS stack: dataset generation, cloud training and evaluation pipelines, and tooling/frameworks so ML engineers can iterate on perception, prediction, and planning models shipped to millions of vehicles. Requires 10+ years software engineering, 4+ years Python/PyTorch/TensorFlow and MLOps; hybrid with 3 days/week in the Nihonbashi, Japan offi
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