Senior Deep Learning Algorithm Engineer

NVIDIA

Senior engineer advancing NVIDIA’s Dynamo open-source distributed inference platform for large-scale, low-latency AI services. Optimizing runtimes, scheduling, networking, and ML inference performance.

Posted 8/5/2026full-timeSanta Clara • California • 🇺🇸 United StatesSenior💰 $152,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing AI inference systems, with strong programming skills in Python, Rust, and C++. Proven ability to collaborate across teams and engage with open-source communities to enhance performance and reliability.

Highest-signal resume keywords

Python ProgrammingRust ProgrammingC++ ProgrammingAI Inference OptimizationOpen-Source Contributions

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Dynamo IntegrationsPerformance ProfilingDebugging Distributed SystemsML ArchitecturesInference TechniquesLatency OptimizationThroughput ImprovementReliability EnhancementAutoscalingKV Caching

Soft Skills

High AgencyLeadership in Ambiguous Work

Tools & Technologies

AI AcceleratorsOpen Source Frameworks

Industry Keywords

Machine LearningDistributed SystemsPerformance-Critical SystemsResearch in ML Inference

Tech Stack

Tools & technologies

Distributed SystemsOpen SourcePythonRust

About the role

Key responsibilities & impact

Design, build, and maintain Dynamo integrations for open source frameworks vLLM, SGLang, and TRTLLM
Partner with open source communities to improve latency, throughput, reliability, and efficiency
Showcase NVIDIA token/watt leadership on public and private benchmarks
Find and remove bottlenecks across runtimes, kernels, networking, routing, and orchestration
Develop inference optimizations for scheduling, disaggregation, KV caching, and autoscaling
Collaborate across research, software, systems, and hardware teams
Engage with the broader ecosystem and external partners to advance AI inference deployment

Requirements

What you’ll need

BS, MS, PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field, or equivalent experience
3+ years building, profiling, and debugging performance-critical distributed or ML systems
Strong programming skills in Python and/or Rust, and C++
Understanding of modern ML architectures and inference techniques
High agency and track record of leading ambiguous work end to end
Experience with AI accelerators
Open-source contributions or leadership
Research in ML inference or distributed systems

Benefits

Comp & perks

Equity
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