Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Build and optimize scalable systems for training and deploying large language models, collaborating with research and infrastructure teams to push AI capabilities in production.
Research and train large language models and Mixture-of-Experts architectures to generate trading signals from financial time-series data on a GPU cluster.
ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology can change lives for the better. It can heal us, entertain us, and make us more connected, productive, and understanding of the world around us. And…
Lead the development of Grab’s proprietary foundation models and generative recommendation systems, scaling distributed training and deploying AI solutions for millions of users.
Position Summary As a Senior Deep Learning Engineer on the Football Modeling side, you'll work closely with our research team on player tracking data, evaluation, and forecasting models. You'll be a senior…
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 Neuron, AWS’s ML compiler/runtime for training GenAI models on Trainium chips, tuning parallelism and kernels across PyTorch/JAX to maximize throughput.
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.
Build and own the shared AI platform that trains and serves Adobe’s generative AI products at global scale, focusing on GPU fleet utilization, model serving, and distributed systems for low-latency inference.
What You'll Do: Looking for an opportunity to apply your technical expertise to a mission that matters, this is it. As the Senior System Administrator , you will support the systems and technologies that power the…
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.
Develops high-performance kernels, compilers, and communication libraries to optimize AI workloads on GPU clusters, focusing on low-latency and memory efficiency.
Lead the design and operation of high-performance AI cluster networks, focusing on InfiniBand/RoCE fabrics, RDMA performance, and fabric reliability for large-scale training and inference workloads.
Lead the design and optimization of large-scale distributed AI training systems, improving performance and scalability for advanced neural networks across GPU clusters.
Build and scale the distributed data infrastructure that powers AI training pipelines and multimodal data catalogs handling petabytes of data.
Build and train ML models that power real-time quantitative trading systems, working with PyTorch/JAX and distributed compute platforms in a fast-paced finance setting.
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.
We couldn't check your fit for this role — add a CV to your profile to see it next time.
