Senior DevTech Compute Eng - GPU Data Processing Remote

Ladders; United States; On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Hybrid work

Equity

Tech access

Job summary

Ladders is seeking a Senior Devtech Compute Engineer specializing in compression and data processing to join a leader in Telecommunications & Hardware. Remote within the US; build data-driven insights, prototype GPU-accelerated methods, and collaborate with cross-functional teams.

You'll analyze workloads, optimize performance, engage with customers, and promote open standards. Requires advanced degree and 5+ years in parallel programming; strong C/C++ and knowledge of CPU/GPU architectures.

Qualifications

• Masters or PhD in Computer Science, Computer Engineering, Applied Math, or related computational field (or equivalent experience).
• 5+ years of relevant experience with a history of complex projects and effective prioritization.
• Hands-on expertise in low-level parallel programming.
• Fluency in C/C++, algorithms, and data structures.
• Knowledge of CPU/GPU/NPU architectures and memory subsystems.
• Domain expertise in data processing, compression techniques, and distributed databases.

Responsibilities

• Prototype novel GPU-accelerated distributed data processing methods.
• Analyze and optimize complex data workloads for performance.
• Collaborate with cross-disciplinary teams to influence hardware and software design.
• Engage with top-tier customers to integrate advanced solutions.
• Promote open standards in data analytics and compression solutions.

Skills

C/C++

Algorithms

Data structures

Parallel programming

CPU/GPU architectures

Education

Master's degree

PhD

Job description

Ladders is seeking a Senior Devtech Compute Engineer specializing in compression and data processing to join a leader in Telecommunications & Hardware. Remote within the US; build data-driven insights, prototype GPU-accelerated methods, and collaborate with cross-functional teams.

You'll analyze workloads, optimize performance, engage with customers, and promote open standards. Requires advanced degree and 5+ years in parallel programming; strong C/C++ and knowledge of CPU/GPU architectures.