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Designs and builds distributed systems for training and deploying machine learning models in a fast-paced San Francisco studio, using Python or Go.
Build and deploy production-grade ML models in San Jose, scaling distributed training across multi-GPU clusters and optimizing performance for low-latency serving.
Builds and optimizes the AI simulation platform that powers Simile’s generative-agent society models, focusing on distributed training, inference, and ML infrastructure to enable fast, cost-effective research-to-production pipelines.
Digital Software Engineer Lead Analyst Vice President Location: Jacksonville, Florida, United States, Irving, Texas, United States Employment Type: Regular Overview of the Role: Citi, the leading global bank, has…
About the Role Applied AI at Uber builds intelligent systems that power critical product experiences across the platform. As a Senior Machine Learning Engineer — Computer Vision, you will develop and deploy…
Design and run ML experiments to create rigorous AI evaluation benchmarks, implementing models in Python and analyzing their performance for frontier systems.
Build and deploy AI models for 3D medical imaging to speed up clinical trials; core tech includes PyTorch, ONNX, TensorRT, Docker, and cloud ML pipelines.
Principal AI/ML Engineer defines enterprise-wide AI architecture, standards, and roadmap, leading large-scale LLM, Agentic AI, and MLOps/LLMOps platforms.
Build and maintain large-scale ML infrastructure for training data pipelines, distributed training workflows, and experimentation systems using PyTorch, Ray, and Airflow.
Designs and optimizes high-performance AI infrastructure for large-scale GPU clusters, working with top tech companies to accelerate generative AI workloads and reduce costs.
Build and maintain the end-to-end robot-learning pipeline, ensuring reliability, reproducibility, and measurability from data collection to real-robot evaluation for a next-gen generalist robotics company.
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience programming in Java, C++, Python or related language - Experience in patents or publications at top-tier peer-reviewed…
- 3+ years of engineering team management experience - 7+ years of working directly within engineering teams experience - 3+ years of designing or architecting (design patterns, reliability and scaling) of new and…
- 7+ years of technical specialist, design and architecture experience - 7+ years of external or internal customer facing, complex and large scale project management experience - 5+ years of software development with…
Design and own end-to-end AI compute solutions for enterprise and AI lab customers, from technical discovery and POCs to production deployment and growth, while building the playbooks and assets that define how Andromeda works with customers.
Optimizes deep-learning pipelines and GPU frameworks to speed up AI-driven trading strategies, working with PyTorch, JAX, CUDA and low-level GPU programming.
Build and maintain large-scale compute infrastructure and ML libraries for Optiver's new AI Lab, supporting PB-scale data model training and simulations using CPU/GPU clusters, containerization, and distributed training algorithms in a fintech trading environment.
Principal ML Engineer New York, NY (Hybrid) About the Company We're building AI-native enforcement infrastructure for enterprise communication — technology that catches and fixes compliance issues in real time,…
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.
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