Staff Inference Engineer

Posted Yesterday
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Palo Alto, CA, USA
In-Office
200K-350K Annually
Senior level
Artificial Intelligence • Machine Learning
Uniphore is the Business AI Company powering the agentic enterprise.
The Role
Build and optimize a context-aware inference runtime for fine-tuned small language models across cloud, on-premises, NVIDIA, and AMD environments. Responsibilities include KV-cache management, speculative decoding, GPU kernel optimization, continuous batching, quantization, multi-GPU execution, adapter lifecycle management, observability, tenant isolation, reliability, and safe deployment. The role partners with research, model engineering, agent, knowledge systems, and platform teams.
Summary Generated by Built In

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.


Job Description:
 

Staff Inference Engineer –

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 selection, and reasoning effort to each task.

KV-cache and computation optimization: Build paged KV-cache and prompt-prefix-cache management, cache-aware routing, retention, eviction, and offloading. Preserve correctness as context, permissions, model versions, and adapters change.

Inference performance: Implement and tune speculative decoding, attention kernels, continuous batching, quantization, chunked prefill, and multi-GPU parallel execution.

SLM and adapter lifecycle: Build model and adapter lifecycle management, multi-adapter serving, zero-downtime hot swapping, and resource scheduling.

Production reliability: Implement observability (DCGM, Prometheus, Grafana), tenant isolation, overload protection, failure recovery, and safe rollout and rollback.

Cross-environment deployment: Build portable runtime integrations across NVIDIA and AMD GPU pla4orms, cloud and on-premises environments, and single- or multi-GPU configurations.


Technical Expertise

Model inference internals: Autoregressive generation, prefill vs. decoding, attention architectures, compute- vs. memory-bound execution, numerical precision.

Speculative decoding: Draft-and-verify execution, acceptance/rejection sampling, adaptive speculation, and throughput tradeoffs.

GPU kernels: Flash attention-style kernels, tiling, operator fusion, memory access patterns.

CUDA, HIP, Triton, or CUTLASS proficiency.

KV and prefix caching: Paged KV storage, fragmentation, cache quantization, offloading, cross request prefix reuse, tenant isolation.

Context-window management: Token budgeting, context selection, prompt compression, conversation compaction, sliding window and sparse attention.

Serving and scaling: Continuous batching, chunked prefill, admission control, quantization, multi-GPU parallelism, prefill/decode disaggregation.


Qualifications Required:

• 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

 

Preferred:

• Custom GPU kernel development (CUDA, HIP, Triton, CUTLASS)

• PyTorch internals — torch. Compile, custom operators, MoE or disaggregated

prefill/decode

• LoRA/SLM adapter serving and zero-downtime hot swapping

• NVIDIA and AMD Instinct hardware in production

• Telemetry with DCGM, AMD SMI, Prometheus, and Grafana


Comp range/OTE: 190- 240K USD


 


Hiring Pay Range:

$200,000 - $350,000

Benefits:


In addition to competitive base pay, this position also includes an annual incentive opportunity based on target achievement,  pre-IPO stock options, benefits including medical, dental, vision, 401(k) with a match, and more, plus generous paid time off, paid holidays, paid day off for your birthday and other paid leave policies to support employees through all phases of life.


Location preference:

USA - CA - Palo Alto

Uniphore is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
 
For more information on how Uniphore uses AI to unify—and humanize—every enterprise experience, please visit www.uniphore.com.

Skills Required

  • 5+ years of engineering experience, including 3+ years of hands-on experience with GPU systems, distributed inference, or ML serving
  • Production experience with vLLM, SGLang, or TensorRT-LLM
  • Strong Python and C++ skills, including C++17 or C++20
  • Ability to read and debug CUDA C++ or HIP kernels
  • Hands-on GPU profiling and performance optimization experience
  • Custom GPU kernel development using CUDA, HIP, Triton, or CUTLASS
  • PyTorch internals, including torch.compile, custom operators, mixture-of-experts, or disaggregated prefill/decode
  • LoRA or SLM adapter serving and zero-downtime hot swapping
  • Production experience with NVIDIA and AMD Instinct hardware
  • Telemetry experience with DCGM, AMD SMI, Prometheus, and Grafana

Uniphore Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Uniphore and has not been reviewed or approved by Uniphore.

  • Healthcare Strength — Health coverage includes medical, dental, vision, mental‑health resources, and wellness programs, with multiple plan options (including HSA/FSA) indicating robust depth. Plan quality and affordability are highlighted relative to peers.
  • Leave & Time Off Breadth — Time off includes generous PTO, paid holidays, and a paid birthday day off. Enhanced parental, caregiver, and bereavement leave extend coverage beyond standard policies.
  • Retirement Support — Retirement offerings include a U.S. 401(k) with company match and pension/retirement plans with employer contributions in many countries. These programs support longer‑term financial security alongside core pay.

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The Company
HQ: Palo Alto, CA
465 Employees
Year Founded: 2008

What We Do

The Business AI Cloud is the only sovereign, composable and secure AI platform that enables businesses to rapidly adopt, significantly transform and immediately unlock the value of their data. Trusted by more than 2,500 of the world’s largest enterprises and recognized by Gartner, Forrester, IDC and the Deloitte Fast 500, Uniphore is where enterprise AI moves from ambitions to production. A Complete, Composable Platform Uniphore is designed to be: Sovereign — run on any public cloud, private cloud or on-premises with full control over your data and AI models. Composable — choose your layer, model, or component—vector DBs, knowledge graphs, data compute, and beyond. Secure — embedded guardrails, observability, and AI security ensure trusted, compliant, and enterprise-grade protection. Trusted at Scale Over 2,000 global businesses — including many of the Fortune 500 — rely on Uniphore every day to drive growth, improve efficiency, and deliver personalized customer experiences. Customers include leaders across industries, like Skechers, LastPass, Atlassian, HP, Allstate, Sony, and more. Industry Recognition Named to Inc.'s Best in Business List Listed on the Deloitte Technology Fast 500 Recognized in reports by Gartner, Forrester, and IDC From Pilot to Production Through strategic collaborations with industry leaders like KPMG, Cognizant, Rackspace, Databricks and Snowflake, Uniphore helps organizations move beyond experimental AI pilots to production-grade deployment — operationalizing AI agents across internal and client-facing workflows at scale.

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