San Francisco, CAUSAgreenhouse2026-06-08
Why this is a real AI job: Die Rolle ist eindeutig auf führende Forschung in KI, insbesondere in Generative AI, Agenten und RL-Systemen ausgerichtet. Die Aufgaben beinhalten die Leitung einer Forschungsgruppe, die Entwicklung von Forschungsroadmaps und die Umsetzung von Prototypen in r…
Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. Our teams operate at the intersection of cutting-edge research, large-scale engineering, and real-world deployment, partnering with leading frontie…
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Zscaler · Office - Bangalore, India
95/100
Office - Bangalore, IndiaUSAgreenhouse2026-07-31
Why this is a real AI job: The role explicitly focuses on developing and deploying machine learning models and Generative AI solutions, specifically Agentic AI architectures. The job description emphasizes LLMOps, productionization of AI agents, and optimization of ML models.
About Zscaler Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange…
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Remote - IndiaUSAgreenhouse2026-07-31
Why this is a real AI job: The role explicitly focuses on building, deploying, and maintaining machine learning systems in production. The responsibilities are heavily centered around ML engineering tasks like model training, validation, data pipeline construction, and collaboration wi…
Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work ,…
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New York, NYSwedenlever2026-07-31
Why this is a real AI job: The role explicitly focuses on building and evolving machine learning models for personalized experiences, including recommendation systems and large language models. The description highlights a strong emphasis on taking models from research to production at…
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep…
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Reddit · Remote - United States
95/100
Remote - United StatesUSAgreenhouse2026-07-31
Why this is a real AI job: The role explicitly focuses on building and deploying ML models, specifically LLMs, for safety systems. The responsibilities are heavily centered around AI/ML tasks.
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximatel…
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United StatesUSAgreenhouse2026-07-31
Why this is a real AI job: The role explicitly focuses on architecting and implementing machine learning solutions, including recommendation engines, ranking systems, and LLMs. It involves leading ML, Data and Product engineers and spearheading ML applications. The description clearly…
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible f…
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P-1 AI · San Francisco Bay Area
95/100
San Francisco Bay AreaGermany/USAFullTimeashby2026-07-31
Why this is a real AI job: The role is explicitly focused on building and improving an AI agent (Archie) for engineering tasks. The description details work with LLMs, agentic harnesses, model training, and production deployment of AI systems. This is a core AI research and engineering…
TL;DR: If you: - have a demonstrated track record of turning ambitious AI ideas into products people actually use; - move effortlessly between research and engineering; - have shipped something extraordinary, at work or outside of it; - are relentlessly curious about how things work… … you should a…
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US and Canada OfficesUSAFullTimeashby2026-07-31
Why this is a real AI job: The role explicitly focuses on applying and improving machine learning techniques (specifically LLMs) at scale. Responsibilities center around building ML pipelines, optimizing models, and working with large datasets – all core AI activities.
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transfor…
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Redwood City, CAUSAFullTimeashby2026-07-31
Why this is a real AI job: The role is explicitly focused on building and maintaining infrastructure for ML research and serving, with a strong emphasis on large language models and GPU utilization. The requirements and responsibilities directly relate to core AI/ML engineering tasks.
ABOUT THE ROLE We’re looking for seasoned ML Infrastructure engineers with experience designing, building and maintaining training and serving infrastructure for ML research. Responsibilities: - Provide infrastructure support to our ML research and product - Build tooling to diagnose cluster issues…
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RemoteUSAgreenhouse2026-07-31
Why this is a real AI job: The role is entirely focused on the development and optimization of LLM inference frameworks, distributed systems, and related technologies. The responsibilities and requirements clearly indicate a core AI/ML engineering position.
About the Role At Together.ai, we are building state-of-the-art infrastructure to enable efficient and scalable inference for large language models (LLMs). Our mission is to optimize inference frameworks, algorithms, and infrastructure, pushing the boundaries of performance, scalability, and cost-e…
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