Software Engineer, Performance Instrumentation

NVIDIA

. Define and maintain performance data requirements from profiling libraries, annotation APIs, frameworks, runtimes, communication libraries, schedulers, configurations, and infrastructure telemetry .

Posted 10/31/2026full-timeUnited StatesSeniorLead💰 $168,000 - $270,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in performance data requirements, instrumentation, and data quality management within machine learning and systems software. Proficient in collaborating across teams to address visibility gaps and ensure effective solutions.

Highest-signal resume keywords

Bachelor's Degree In Computer Science8+ Years Of Software Engineering ExperienceProficiency In CUDAExperience With Machine Learning FrameworksStrong Debugging Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

InstrumentationTracingData Quality ManagementPerformance MeasurementCode ReviewAutomated Development ToolsPythonC++

Soft Skills

Excellent Communication Skills

Tools & Technologies

PyTorchJAXNVTX

Industry Keywords

Machine LearningSystems SoftwareData ValidationTelemetryAnnotation APIs

Tech Stack

Tools & technologies

PythonPyTorchC++

About the role

Key responsibilities & impact

Define and maintain performance data requirements from profiling libraries, annotation APIs, frameworks, runtimes, communication libraries, schedulers, configurations, and infrastructure telemetry
Identify and prove visibility gaps with concrete evidence
Collaborate with relevant teams to address visibility gaps or build solutions
Inform the development of low-overhead instrumentation and annotation APIs
Ensure data quality at ingestion through validation, sanitization, checks, and alerting mechanisms
Measure and manage instrumentation overhead and observer effects on real workloads
Collaborate with multiple partner teams, manage commitments, and ensure continuous progress

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience
8+ years of relevant software engineering experience
Hands-on experience with instrumentation or tracing in production machine learning or systems software
Proficiency in CUDA
Working knowledge of machine learning frameworks such as PyTorch or JAX
Experience with annotation or tracing APIs such as NVTX
Experience maintaining data quality in a pipeline, including validation, checks, alerting, and provenance
Experience measuring instrumentation overhead and making trade-offs among overhead, fidelity, sampling, and aggregation
Experience implementing modifications in code managed by other groups
Strong debugging skills across component boundaries
Ability to validate changes through code review, tests, and independent measurements, including automated development tools
Excellent communication skills
Proficiency in Python and C++

Benefits

Comp & perks

Equity
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