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Platform Engineer owning the platform layer between researchers and GPU infrastructure—Kubernetes clusters, CI/CD pipelines, cloud-as-code, and security standards—using Terraform, Prometheus, and Grafana at an AI safety nonprofit.
About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment,…
Hands-on Senior ML Engineer on a 5-person data science team at Oschadbank, designing and productionizing propensity models (custom PyTorch ensembles, XGBoost/LightGBM) for credit, card, and deposit products, with upcoming LLM work (fine-tuning, RAG). Stack: Oracle/ClickHouse, Feast, Airflow, MLflow/DVC, Docker, GitLab CI.
Leads AI-driven recommendation systems for an e-commerce platform, designing multimodal search and personalization models using Google's Vertex AI and TensorFlow.
Build and scale Oracle’s managed Kubernetes service (OKE), designing distributed systems for cluster lifecycle, networking, storage, and AI/GPU workloads while leading cross-team technical initiatives.
AI Engineer *PhD Required Employment Type: Full-Time Location: Remote, Pakistan Transform AI Research into Real-World Impact As an AI Research Engineer at Pixalate, you'll bridge the gap between fundamental AI…
AI Infrastructure Engineer 5 days, Mon - Fri 8.30am to 5.30pm Salary: $5,000 to $7,000 Location: Kaki Bukit Ave Job scopes: Compute & Cluster Management Architect, configure, and maintain high-density multi-GPU…
About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated…
At Amazon, our tech isn't just a tool, it's your playground. Our engineers work on scalable systems, cloud services, and customer-facing products that operate at global scale. This is an environment where you…
Senior Computer Vision Engineer - Deep Learning Salary: £70,000 to £95,000 Location: West London Working arrangement: Predominantly office and customer-site based, with some remote working available Employment:…
The Oracle Cloud Infrastructure (OCI) team offers the opportunity to build and operate massive-scale, integrated cloud services in a broadly distributed, multi-tenant cloud environment. OCI builds cloud products for…
Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial…
Lead the design, development, and production deployment of AI/ML solutions for document understanding — image classification, text categorization, and data extraction from scanned TIF documents — within JPMorgan's Healthcare Provider team. Core stack: Python, PyTorch/Transformers, computer vision and OCR, AWS SageMaker, Bedrock, and EKS-based microservices.
Infrastructure engineer at Causal Labs (AI startup) building and optimizing large distributed ML training and inference clusters for a Large Physics foundation Model, starting with weather prediction. Core stack: FSDP, DeepSpeed, NVIDIA GPUs, Python/C++, Kubernetes, Docker, GCP/AWS/Azure; on-site in San Francisco 5 days a week.
Machine learning researcher at Causal Labs (via Transparent Search Group) building a Large Physics foundation model starting with weather, working across the full ML stack — data pipelines, novel architectures, training, and evaluation — in Python/PyTorch on 100s–1000s of GPU clusters. Onsite in San Francisco 5 days a week.
Dyna Robotics is hiring an ML Infrastructure Engineer in Redwood City (in office 5 days/week) to own training infrastructure end to end: scaling distributed training across multi-cloud GPU fleets, building scheduling tooling, and optimizing low-latency inference for robot control. Core stack includes PyTorch, FSDP/ZeRO, Kubernetes, SLURM, CUDA, and TensorRT/Triton.
Program manager inside AMD's AI Research org, turning reinforcement-learning, post-training, and hardware-research agendas into executable plans: tracking milestones, coordinating scientists, infra engineers, and hardware teams, and managing GPU compute for large-scale experiments. Needs strong program management plus ML/RL/LLM fluency and executive communication skills.
Build and maintain MLOps infrastructure for freight-intelligence models, automating monitoring, retraining, and deployment at scale in a logistics-focused product team.
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