Jobs Referso Partner API

Free job alerts

GPU performance optimization jobs

Job titleLocation

Popular:United States Canada Viet Nam

All filtersRefine by skill, company, date, job type, industry and more

Company

Skillsjobs that use all of them

GPU performance optimization

Popular

Date posted

Any timePast hourPast 24 hoursPast week

Workplace

RemoteHybridOn-site

Job type

Full-timePart-timeContractInternshipTemporary

Experienceyears required

0–2 years2–5 years5–10 years10+ years

Salary

Salary listed

Education

High schoolAssociate degreeBachelor's degreeProfessional certificatePostgraduate degree

Industryfield of work

Software & InternetHardware & ElectronicsEngineeringHealthcareLife Sciences & ResearchFinance & AccountingSales & Business DevelopmentMarketing & CommunicationsCreative & DesignCustomer Service & SupportAdministrative & OfficeHuman Resources & RecruitingLegal & ComplianceManagement & OperationsEducation & TrainingRetailHospitality & Food ServiceManufacturing & ProductionSkilled Trades & ConstructionTransportation & LogisticsFacilities, Cleaning & SecuritySocial Services & Public SectorEnergy, Environment & Agriculture

1 selected

Skill:GPU performance optimization

Referso Jobs

Fresh jobs from employer career sites in the US and Europe. Search free, get alerts free, and let Referso apply when you're ready.

Job seekersSearch jobs Free job alerts Remote jobs Jobs by location Jobs by skill

RefersoAuto-apply How it works Pricing Log in

For companiesPartner API (beta)API docs Contact sales

CompanyAbout Contact Privacy Terms

© 2026 Referso. Jobs link to the original posting; Referso is not affiliated with the employers listed.Privacy Terms Request a removal

1–2 jobs· newest first

GPU High-Level ModellingNew
Qualcomm · San Diego, US
$141K–$212K
Machine Learning Infrastructure Engineer
True Talent Solutions Partners · San Francisco, US
$200K–$400KOn-site · Full-time · Senior

+10K new in the last hour

GPU High-Level Modelling

Qualcomm · Posted Nov 13, 2026

San Diego, California, United States
$141K–$212K per year
4+ years

Apply with Referso

AI

Apply on careers page

Lead GPU engineering design, implementation, verification, and optimization of GPU cores.

Compensation

$141,300.00 - $211,900.00

Responsibilities

Architect, design, implement, verify, and optimize GPU core performance and power
Build functional model simulations, develop software, and test graphics for correctness and performance
Design, program, and run comprehensive graphics tests using tools and benchmarks
Collaborate with cross-functional teams, vendors, and users to guide implementation
Develop critical driver and compiler software to support GPU products

Requirements

Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field
Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field
PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field
Nice to have: GPU experience
Nice to have: Senior leadership interaction

Skills

GPU architecture GPU performance optimization GPU power optimization GPU core design GPU verification GPU simulation GPU testing driver development compiler development graphics benchmarks software development Software development tools Driver development tools Compiler tools Graphics testing tools Benchmarking tools

Benefits

Competitive annual discretionary bonus program
Annual RSU grants
Comprehensive benefits package

See full job description

T

Machine Learning Infrastructure Engineer

True Talent Solutions Partners · Posted Nov 12, 2026

San Francisco, California, United States
On-site
Full-time · Senior
$200K–$400K per year
2–10 years

Apply with RefersoAI Apply on careers page

Build the infrastructure that enables scalable model training and inference for large foundation models applied to physical systems, such as weather.

Compensation

Base salary range: $200,000 to $400,000 USD annually. Visa sponsorship is not available.

Responsibilities

Design, deploy, and maintain distributed machine learning training and inference clusters
Build scalable end-to-end pipelines for large datasets and model training across the machine learning lifecycle
Test training approaches, including parallelization methods and numerical precision trade-offs across model scales
Profile and debug low-level GPU operations to improve performance
Follow relevant research and apply useful ideas to infrastructure and training workflows

Requirements

Nice to have: Physical AI
Nice to have: AI for science
Nice to have: Robotics
Nice to have: Biology

Skills

Python C++GPU performance optimization CUDA JAX

Benefits

Relocation support

See full job description