MUST HAVE EXPERIENCE WITH**SPECIFIC COMPANIES** AND A DEGREE FROM **SPECIFIC UNIVERSITIES** (LISTED BELOW).
Excellent oral and written communication skills, capable of providing clear and structured evaluation rationales.
Candidates must have **experience as an employee** working for at least one of these companies in the last seven years: Google, Alphabet, Apple, Amazon, Meta, Facebook, Netflix, Microsoft, Tesla, NVIDIA, Adobe, Salesforce, Airbnb, Dropbox, Stripe, Palantir, Uber, Lyft, Square, Block, Twilio, Snap Inc., Pinterest, GitHub, Atlassian, HashiCorp, Databricks, Snowflake, Cloudflare, DigitalOcean, MongoDB, Elastic, Confluent, Figma, Oracle, Cisco, Paypal, Doordash, Rivian, Reddit, Coinbase, Splunk, Goldman Sachs, Morgan Stanley, JPMorgan Chase, Capital One, Plaid, Shopify, Intuit, Workday, Spotify, ServiceNow, Hugging Face, VMware, Brex, Wise, Epic Games, Unity Technologies, Activision Blizzard, Riot Games, Valve, Huawei, Bloomberg, ByteDance, Alibaba, Baidu, Notion, Klarna, Instacart, Zillow, Ramp, Datadog, or IBM Research.
Deep understanding of software architecture, design, development, debugging, and code quality assessment.
Demonstrated experience in application development and deploying scalable, production-grade software.
Candidates must be based in the United States
5+ years of software engineering experience.
Strong expertise in Python, JavaScript (including ReactJS), C/C++, Java, Rust, and Go.
Candidates must have a degree from one of the following universities to be considered for this role: Princeton University, Massachusetts Institute of Technology (MIT), Harvard University, Stanford University, Yale University, California Institute of Technology (Caltech), Duke University, Johns Hopkins University, Northwestern University, University of Pennsylvania, Cornell University, University of Chicago, Brown University. Columbia University, Dartmouth College, University of California, Los Angeles (UCLA), University of California, Berkeley (UC Berkeley), Rice University, Carnegie Mellon University, University of Michigan, Ann Arbor, Washington University in St. Louis, University of North Carolina, Chapel Hill, University of Southern California, University of California, San Diego, New York University, University of Texas, Austin, Georgia Institute of Technology, University of California, Davis, University of Illinois, Urbana-Champaign, or University of California, Irvine.

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Software Development Engineer 2 [208853]

Aquent Talent

Chicago, IL

$48/hr

RemoteFlexible ScheduleHealth InsurancePaid Time OffRetirement Benefit

Hands-on experience with profiling tools and interpreting timing/counter data.
Bachelor's degree in computer science, software engineering, or a relevant field.
Familiarity with a broad range of graphics and performance analysis tooling.
Proven experience identifying performance bottlenecks through trace collection and in-depth analysis.
2-4 years of experience in software development or performance analysis.
Hands-on graphics experience beyond generic software engineering.
Comfortable working in various operating environments (command line basics, driver/runtime builds) and strong written communication for bug reports and triage summaries.
Hardware architecture knowledge relevant to graphics processing.
Strong understanding of real-time rendering fundamentals and the GPU graphics pipeline (draw calls, state changes, shaders, textures, buffers).
Understanding of GPU architecture basics (waves/warps, occupancy, caches, memory bandwidth) and shader instruction set architecture at a high level.
Comfortable working in server environments (shell, services, and basic scripting).
Familiarity with modern graphics API concepts (e.g., command queues/lists, descriptor heaps, resource states/barriers) and basic shader concepts in common shader languages.
Scripting for automation (e.g., Python, PowerShell, Bash) and basic data analysis (e.g., spreadsheets, simple plots).
Proficiency in C/C++ with the ability to read and reason about performance-sensitive code.
Exposure to graphics stack concepts and debugging (e.g., display driver models, graphics infrastructure, event tracing, driver symbol debugging).