Define and execute Alluxio’s AI systems strategy, bridging AI infrastructure and distributed data systems.
Posted by employer 1 year ago
First seen on Joblaze 1 week ago
Last verified on the company career page 3 days ago
Not disclosed in this posting: compensation, years of experience, work arrangement, visa sponsorship.
Joblaze summary
The Technical Product Manager at Alluxio focuses on shaping the company's AI systems strategy, working daily to enhance features that optimize latency, throughput, and GPU efficiency for model training and inference. This role requires a strong understanding of AI infrastructure and distributed data systems, as well as collaboration with engineering and research teams. It is well-suited for someone with a background in product management and a deep knowledge of AI technologies. Alluxio's innovative environment, backed by prominent investors, positions it at the forefront of data orchestration for AI.
From the original posting
About Alluxio:
Alluxio powers the data layer for modern AI and analytics. Proven in production at eight of the top ten internet companies and seven of the ten highest-valued enterprises globally, Alluxio’s open-source data-orchestration platform unifies data across storage systems, regions, and clouds — enabling memory-speed access for large-scale AI and analytics workloads.
Spun out of UC Berkeley’s AMPLab and backed by Andreessen Horowitz, Hillhouse Capital, and Seven Seas Partners, Alluxio sits at the intersection of data, distributed systems, and AI infrastructure.
Our technology is deployed at scale by Meta, Uber, TikTok, Alibaba, Microsoft, and Salesforce, orchestrating data for billions of operations per day.
Learn more at alluxio.io or on Wikipedia.
The Role
We’re hiring a Technical Product Manager to define and execute Alluxio’s AI systems strategy — spanning inference, training, and emerging agentic workloads.
This role bridges the worlds of AI infrastructure and distributed data systems, guiding how Alluxio evolves to serve next-generation model architectures and large-scale data flows.
You’ll partner with engineering, research, and enterprise AI teams to build features that improve latency, throughput, and GPU efficiency for model inference and training — and design the data layer powering the shift toward autonomous, agentic AI systems.