GPU Software Engineer (Remote - US) at Jobgether

, , United States -

Full Time

Start Date

Immediate

Expiry Date

11 Jan, 26

Salary

227200.0

Posted On

13 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

GPU Programming, Parallel Computing, C++, CUDA, Python, Deep Learning, PyTorch, JAX, TensorFlow, Neural Network Modeling, Linux Systems Programming, Performance Optimization, Problem-Solving, Communication, Collaboration

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a GPU Software Engineer in the United States. We are seeking a GPU Software Engineer to develop high-performance, GPU-accelerated software for real-time DNA sequencing analysis. This role involves implementing neural network algorithms on GPU architectures, optimizing data processing pipelines, and supporting the deployment of cutting-edge diagnostic technologies. You will collaborate with cross-functional teams, research and design innovative solutions, and ensure high-quality, maintainable software. The position requires deep knowledge of GPU programming, parallel computing, and machine learning frameworks. This role offers the opportunity to contribute to life-changing healthcare solutions while working in a collaborative and fast-paced environment. Remote work is possible for exceptional candidates, though proximity to the Bay Area, California is preferred. Accountabilities Develop GPU-accelerated software for real-time data analysis on sequencing instruments. Implement and optimize neural network algorithms for high-throughput processing. Write, debug, and maintain high-quality, object-oriented C++ and CUDA code. Collaborate with teams to integrate software with hardware and ensure system-level performance. Participate in research and design to resolve complex technical challenges and improve performance. Support software deployment, testing, validation, and post-go-live troubleshooting. Apply best practices in coding, documentation, and software design to ensure maintainability and reliability. Bachelor’s degree in Computer Science, Computer Engineering, or a related field; MS/PhD preferred. 5+ years of experience in GPU programming and parallel computing. Expertise in C++ and CUDA; familiarity with Python for modeling tasks. Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow. Understanding of neural network modeling, training, and inference optimization on GPUs. Advanced knowledge of Linux systems programming and performance optimization. Strong problem-solving skills, ability to work independently, and manage multiple priorities. Excellent oral and written communication skills, and ability to collaborate across teams. Willingness to travel occasionally and adapt to fast-paced development cycles. Competitive salary range ($94,500–$227,200, depending on experience, location, and other factors). Potential annual discretionary bonus. Comprehensive benefits package including medical, dental, vision, and prescription coverage. Remote work flexibility for exceptional candidates. Opportunities for professional development and career advancement. Chance to contribute to innovative healthcare technology impacting lives worldwide. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, it is shared directly with the hiring company, who will manage the final selection steps, including interviews and additional assessments. Thank you for your interest! #LI-CL1

Responsibilities

Develop GPU-accelerated software for real-time data analysis on sequencing instruments and implement and optimize neural network algorithms for high-throughput processing. Collaborate with teams to integrate software with hardware and ensure system-level performance.