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Build and optimize scalable systems for training and deploying large language models, collaborating with research and infrastructure teams to push AI capabilities in production.
About the company An AI/ML tech startup developing a novel foundation model with a singular vision: to achieve fully automated, unsupervised software delivery in embedded control systems. Backed by venture capital and…
Build and scale ML systems for ad ranking, bid optimization, and real-time recommendations using PyTorch/TensorFlow to improve CTR, CVR, and ROI in a mobile advertising platform.
Build and optimize ML deployment platforms and inference pipelines for autonomous-vehicle software, shipping PyTorch models to GM’s Super Cruise fleet with real-time latency and safety constraints.
Build and scale ML infrastructure and backend systems for AI-powered marketplace platforms, focusing on reliability, performance, and developer velocity.
Sr Software Engineer - AI Infra - Training About the role and team Leading at Uber means setting direction in motion, not waiting for perfect conditions. As a Sr Software Engineer, you will be a technical anchor for…
Architect and scale ML infrastructure for real-time embedding serving and distributed training systems at Reddit, optimizing low-latency inference and collaborating on ML strategy for personalization.
Build and optimize ML pipelines, design ML platforms for recommendations, and develop serving/monitoring for production ML systems at Reddit.
Build predictive world models using generative AI and deep learning to simulate how scenes evolve, training autonomous driving and robotics policies from multimodal sensor data.
Engineer next-gen AI compute platforms by profiling workloads, tuning clusters, and debugging hardware/software to optimize performance and guide architecture decisions.
Optimize and port AI inference/training kernels across NVIDIA, AMD, TPUs, and emerging accelerators, designing portable abstractions for SGLang and Miles.
Research and engineer next-generation diffusion and flow-based models for image, video, and multimodal generation, scaling training and deployment on GPUs/TPUs.
Build and train vision-language-action models and reinforcement-learning policies for real-world robots, using JAX and distributed training to prototype sim-to-real transfer and dexterous manipulation.
Develops high-performance kernels, compilers, and communication libraries to optimize AI workloads on GPU clusters, focusing on low-latency and memory efficiency.
Responsibilities Team Introduction TT-Search Algorithm & Applied AI is the algorithm team behind the search business built on TikTok (TikTok Search), with the goal of becoming the search engine of choice for users…
Build and deploy NLP pipelines using LLMs for contact-center insights, including text classification, summarization, and agentic applications in a fast-moving AI startup.
Own and optimize the CI/CD infrastructure for SGLang, an open-source LLM inference engine, ensuring fast, reliable, and secure test pipelines across multiple GPU hardware pools.
Build and maintain ML pipelines, deploy models via APIs/containers, and monitor performance for government AI projects using cloud-native tools.
Research and build next-gen AI world models that predict and interact with the real world, focusing on conditioning, control, and scalable training/inference systems.
About VESSL AI AI researchers spend more time fighting for compute than doing research. Quota walls, rigid contracts, and fragmented supply across clouds and clusters mean teams are stuck waiting on a single provider…
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