GPU Software Engineer

CAE • Tampa, FL

1d • Onsite

About The Position

We are seeking a skilled GPU Software Engineer to join our growing AI & Data Science team in R&D. This role is ideal for someone passionate about parallel computing, (General-Purpose computing on Graphics Processing Units) GPGPU programming, and distributed systems to design and optimize high-performance applications. The ideal candidate will have a strong background in scalable architectures, GPU acceleration, and multi-node environments to deliver cutting-edge solutions for compute-intensive workloads. This position is onsite with locations in Tampa FL, Arlington TX, or Orlando FL.

Requirements

• Bachelor’s or Master’s degree in Computer Science, or related field.
• 3+ years of experience in parallel programming, GPGPU computing, and distributed systems.
• Strong understanding of parallel programming concepts, including multi-threading, synchronization, and communication.
• Strong proficiency in C/C++, Python, and parallel programming paradigms.
• Familiarity with virtualization technologies, such as Docker and Kubernetes.
• Hands-on experience with CUDA, OpenCL, or HIP for GPU acceleration.
• Solid understanding of distributed systems, networking, and cluster management tools (e.g., Kubernetes).
• Experience with performance profiling and optimization techniques.
• Understanding of data structures and algorithms, including object-oriented programming.
• Excellent communication and collaboration skills.
• Must comply with all company security and data protection / usage policies and procedures.
• Personally responsible for proper marking and handling of all information and materials, in any form.
• Shall not divulge any information, or afford access, to other employees not having a need-to-know.
• Shall not divulge information outside company without management approval.
• All government and proprietary information will be accessed and stored electronically on company provided resources.
• Incumbent must be eligible for DoD Personal Security Clearance.
• Due to U.S. Government contract requirements, only U.S. citizens are eligible for this role.

Nice To Haves

• Device driver development, including GPU or CPU.
• Knowledge of data exchange standards and APIs, such as DIS.
• Knowledge of containerization and orchestration for workloads.
• Experience with machine learning acceleration on GPUs is a plus.
• Experience with High Performance Computing including parallel and distributed computation is a plus.

Responsibilities

• Design and implement parallel algorithms for large-scale data processing and scientific computing.
• Develop and optimize GPGPU applications using CUDA, OpenCL, or similar frameworks.
• Architect and maintain distributed systems for high availability and fault tolerance.
• Collaborate with cross-functional teams to integrate solutions into production environments.
• Benchmark, profile, and tune performance across heterogeneous computing platforms.
• Stay current with emerging technologies in GPU computing and distributed architectures.

Benefits

• Comprehensive and competitive benefits package and flexibility that promotes work-life balance
• A work environment where all employees are valued, respected and safe
• Freedom to succeed by enabling team members to deliver, take initiatives and make decisions
• Recognition, professional development, advancement and having fun!

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees