We enable businesses to rapidly adopt, significantly transform and immediately unlock value through our Business AI Cloud that is sovereign, composable and secure. Backed by NEA.
About the role
Uniphore is the Business AI company. Our sovereign, composable and secure AI platform connects enterprise data, fine-tunes AI models and deploys agentic AI across the enterprise. We empower every worker to boost productivity and help businesses grow faster, operate smarter and reduce costs. Trusted by more than 2,000 businesses globally, and recognized on the Deloitte Fast 500, Uniphore delivers on the promise of AI as a transformative force for business. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 5+ years engineering, including 3+ years hands-on with GPU systems, distributed inference, or ML serving
- Production experience with vLLM, SGLang, or TensorRT-LLM
- Strong Python and C++ (C++17/20), ability to read and debug CUDA C++ or HIP kernels
- Hands-on GPU profiling and performance optimization
More about this role
Uniphore is the Business AI company. Our sovereign, composable and secure AI platform connects enterprise data, fine-tunes AI models and deploys agentic AI across the enterprise. We empower every worker to boost productivity and help businesses grow faster, operate smarter and reduce costs. Trusted by more than 2,000 businesses globally, and recognized on the Deloitte Fast 500, Uniphore delivers on the promise of AI as a transformative force for business.
Uniphore is building an enterprise AI pla4orm where agents operate across voice, video, text, and structured data in real time. We are looking for a Senior or Staff Inference Engineer to own the inference layer — combining deep model inference expertise with systems engineering to deliver a context-aware runtime serving finetuned SLMs across cloud, on-premises, and widely used GPU platforms.
This is a hands-on individual contributor role working closely with Uniphore’s research, model engineering, knowledge systems, agent, and pla4orm teams.
What You Will Build
Context-aware runtime: Integrate context selection, compression, conversation compaction, and persistent task state with model execution. Adapt context budgets, model...
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