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Own the infrastructure behind Speechmatics' speech AI models: build and maintain scalable data pipelines (including web scraping and data acquisition) and operate the platform that trains, evaluates, and serves models in production. Core stack is Python, SQL, Docker/Kubernetes, cloud, and MLOps/GPU tooling.
Software Engineer II on the Microsoft Turing team building Microsoft 365 Copilot: designing and scaling backend platform, orchestration, and runtime systems that bring LLM-powered AI features to hundreds of millions of enterprise users. Work spans coding, architecture, and testing alongside applied scientists, using languages like C#, C++, Java, JavaScript, or Python.
Shield AI is hiring a system architect to own the architecture of Hivemind Forge, the AI development ecosystem behind its Hivemind autonomy software. Day to day, they define the software, data, and AI/ML architecture that lets teams build, train, evaluate, and deploy AI-driven autonomous capabilities across cloud, HPC, and secure or disconnected environments.
Software Engineer II on Microsoft's Turing team in Bangalore, building production systems behind Microsoft 365 Copilot — including LLM orchestration/runtime, container execution, image generation, and agentic interactions. Day-to-day spans coding, code review, test strategy, safe deployments, and on-call support.
Internship program: 12 - 24 weeks, full-time, in-person in the Berlin office Relentlessly push search quality forward — through models, data, tools, or any other leverage available Train, and optimize large-scale deep…
Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate Job Description & Summary At PwC, our people in data and analytics focus on leveraging…
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JPMorgan Chase within the Commercial and Investment Banking team, you will…
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more…
Job Description GM Vehicle Autonomy is forming a centralized Site Reliability Engineering team to make reliability a measurable, engineered property of the systems used to build, validate, release, and operate…
Builds and operates Kubernetes-based GPU/TPU superclusters across multiple clouds to train, evaluate, and serve Cohere's frontier AI models, optimizing ML workloads for performance, cost, and reliability, and creating self-service tooling for researchers using Python, Go, and technologies like RDMA and NCCL.
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just…
Senior ML engineer on Moveworks' ML infrastructure team (ServiceNow) who builds, optimizes, and scales end-to-end infrastructure for training, evaluating, and serving LLMs in production. Core technologies include PyTorch/Hugging Face, LLM serving frameworks like vLLM and TensorRT-LLM, Python plus C++/Go, and distributed training and inference pipelines.
Leads a team to build and deploy AI systems for computer vision and agentic workflows, including data pipelines, MLOps, and scalable cloud infrastructure.
Build and scale ML infrastructure for brain-computer interface research, including distributed training pipelines, data platforms, and cloud infrastructure to support neuroscientific modeling and neural decoding.
Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production…
Research Engineer at Lightning AI to optimize AI training and inference workloads on PyTorch Lightning infrastructure, improving performance and scalability for production systems.
Own the product vision and roadmap for AI experimentation and post-training tooling, defining workflows for model evaluation, fine-tuning, and deployment while collaborating with engineers and customers to build a cohesive developer experience.
Build backend systems for AI agent orchestration, distributed training, and experiment management using Go/Python/Rust, enabling scalable AI development workflows.
Build and optimize PyTorch-based training and post-training pipelines for large language models, improving model quality and training efficiency while collaborating with research and infrastructure teams.
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