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Internal Coupang transfer role: a Staff ML Engineer on the Coupang Media Group Offsite Ads team in Seattle designs and ships machine learning systems for ad targeting, ranking, bidding, and CTR/CVR prediction, using Python/Java, PyTorch, LLMs, and large-scale ML infrastructure.
Senior engineer on AMD's AI software team in Taipei, optimizing deep learning frameworks such as PyTorch, TensorFlow, and SGLang for AMD GPUs: developing high-performance GPU kernels, scaling training and inference across multi-GPU/multi-node systems, and upstreaming optimizations to open-source projects. Core stack: C++, Python, Linux, HIP/Triton.
Staff PM owning observability as a product across Lambda's AI GPU cloud — deciding what customers see (GPU/cluster health, utilization, job telemetry, InfiniBand metrics) in the console and API, and building the internal telemetry layer with SRE and fleet engineering. Needs 7+ years in product management, 3+ on technical infrastructure or developer-facing products.
Lead ML systems for Roblox’s virtual economy, building large-scale recommendation, ranking, and generative AI pipelines that power personalized experiences across Marketplace, Payments, and Avatars.
Principal ML Infrastructure Engineer at Roblox builds and scales the machine learning systems that power ads and discovery for hundreds of millions of users, using large-scale training, inference, and feature pipelines.
Lead a team of ML engineers and architects at an AI-first cloud services company, owning hiring, team growth, and complex customer engagements while shaping AI/ML architectures and driving pre-sales.
Build and scale Databricks' managed GPU training platform (AI Runtime), designing systems for large-scale AI model training, fault tolerance, and developer experience.
Senior systems engineer based in Munich building the control plane for bare-metal AI/GPU infrastructure: Kubernetes operators and CRDs, GPU cluster scheduling, and driver/fabric tuning for distributed LLM training. Core stack: Python, Linux internals, Kubernetes, NVIDIA GPU tooling, Terraform/Ansible.
Senior AI/ML engineer building and deploying scalable, production-ready AI, ML, and generative AI systems for US federal government clients. Day to day involves Python development, data pipelines, MLOps/CI/CD, APIs and microservices, and model optimization on cloud platforms, requiring an active TS/SCI clearance.
Senior ML engineer builds and deploys scalable AI pipelines for materials, chemistry and physical sciences, using PyTorch, cloud infra and production-grade MLOps.
Build and deploy AI voice and text agents handling millions of customer interactions monthly for Wave’s fintech platform in Africa, using LLMs and speech tech.
Designs and deploys ML models to predict and prevent GPU cluster failures, optimizing real-time AI infrastructure reliability and utilization.
Designs and deploys end-to-end AI infrastructure for enterprises, integrating NVIDIA GPU clusters, high-performance networking, parallel storage, and AI software stacks to support large-scale model training and inference.
Senior engineer on Motorola Solutions' camera systems team designs, optimizes, and deploys AI and computer-vision models in modern C++ directly on embedded camera hardware for real-time safety and security video analysis. Core tech: modern C++, embedded Linux, camera SDKs, performance optimization, and ML deployment.
Senior ML Infrastructure Engineer on Reddit's ML Platform team, building and scaling the infrastructure behind recommendations and content discovery. Day-to-day work spans MLOps lifecycle design, graph ML platform development, distributed GPU training optimization, and large-scale batch data pipelines using Python, PyTorch, Ray, Kubernetes, Spark, and GCP.
Reddit is hiring a Staff ML Systems/Infrastructure Engineer to build and lead the platform powering large-scale ML: MLOps lifecycle tooling, a graph ML codebase, GPU training performance tuning, and pipelines for graph data with billions of nodes. Core stack includes Python, PyTorch/TensorFlow, Ray, Kubernetes, GCP (BigQuery, GCS), Terraform, and Apache Beam/Spark.
Reddit is hiring a founding Staff Machine Learning Engineer on its AI Security team to lead the design, training, evaluation, and deployment of ML models that detect AI-related risks like prompt injection and jailbreaks. Day-to-day involves hands-on model development on Reddit's LLM Guardrails Platform using Python, PyTorch/TensorFlow, and distributed training pipelines, plus technical leadership
Builds the infrastructure, tooling, and optimization systems that let Reddit's ML engineers train, evaluate, deploy, and serve models efficiently — improving GPU utilization, cutting infrastructure costs, and speeding up experimentation. Core stack: Python, systems languages, distributed training frameworks, and GPU/serving platforms.
AI research role at Physical Superintelligence (psi), a startup building agents and RL training systems that learn to do physics. Day to day: train RL agents for scientific discovery, design physics-reasoning benchmarks and reward structures, scale distributed training, and publish results alongside physicists and infrastructure engineers in Boston.
Senior Sales Engineer partnering with Account Executives to drive technical strategy and adoption of Datadog's observability and security platform. Key responsibilities include leading technical evaluations (POVs), delivering product demos, and navigating complex enterprise environments using technologies like AWS, Azure, GCP, and Kubernetes.
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