Staff High-Performance Software Engineer

Atlas Data Storage, Inc.

$170K — $200K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years of experience in high-performance or systems-level software development
  • Expertise in C, C++, or Rust programming languages
  • Strong understanding of CPU/GPU architectures and memory management
  • Advanced knowledge of parallel computing and distributed systems
  • Ability to write optimized code using high-level (e.g., PyTorch) and low-level (e.g., CUDA) frameworks

Responsibilities

  • Architect and implement efficient distributed data processing pipelines
  • Develop optimized pipelines for massive data payloads
  • Collaborate with software and bioinformatics teams for integration within the ecosystem

Benefits

  • Work within a cutting-edge technological environment
  • Opportunity to contribute to impactful projects in data processing
  • Collaborative team culture that fosters innovation
Full Job Description
Role Overview As a Staff High-Performance Software Engineer, you will be a foundational member of our engineering team. You will play a critical role in accelerating our complex encoding and decoding pipelines, leveraging the full computational power of GPUs and CPUs within a distributed system environment.

Key Responsibilities

  • System Architecture: Architect and implement highly efficient, distributed data processing pipelines across hybrid hardware platforms.
  • Performance Optimization: Develop highly optimized pipelines capable of processing massive data payloads with predictable throughput and resources.
  • Cross-Functional Collaboration: Partner closely with our software, and bioinformatics team on integration within our larger ecosystem.


Required Qualifications (Skills & Experience)

  • Experience: 8+ years of professional software development experience in high-performance or systems-level environments.
  • Languages: Deep expertise in systems-level programming languages such as C, C++, or Rust.
  • Hardware Architecture: Strong understanding of CPU/GPU architectures, memory management, and hardware bottlenecks.
  • Domain Knowledge: Advanced knowledge of parallel computing paradigms, concurrency, and distributed system architectures.
  • Compute Frameworks: Proven ability to write highly optimized code using both high-level machine learning libraries (e.g., PyTorch) and low-level kernel development interfaces (e.g., CUDA, OpenCL, or Metal).


Preferred Qualifications

  • Education: Bachelor's or master's degree in computer science, Computer Engineering, or a related highly technical field.
  • Profiling Tools: Familiarity with performance profiling and debugging tools (e.g., NVIDIA Nsight, perf, Valgrind).


The pay range for this role is:

170,000 - 200,000 USD per year (HQ)

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