ABOUT US

Siana Technology, LLC is a small business in Annapolis Junction, MD. We are professional, agile and our goal is to Siana Technology, LLC is a leading provider of cutting-edge solutions in the field of High Performance Computing (HPC), a small business in Annapolis Junction, MD. We specialize in designing and implementing state-of-the-art systems that power critical computational. We are professional, agile and our goal is to provide direct Engineering and Software Development support to the US Government in areas of design and development of mission-focused Systems.

Our work environment includes:

• Modern office setting
• Flexible working hours
• Growth opportunities
• Relaxed atmosphere

**Mandatory: Active TS/SCI + Full Scope Poly
We are seeking a talented Software Engineer to join our dynamic team. As a Software Engineer, you will play a crucial role in designing, developing, and maintaining cutting-edge software solutions. If you are passionate about AI/ML technology, this is the perfect opportunity for you to showcase your skills and contribute to exciting projects.

TECHNICAL SKILLS:

• Familiarity with ML Frameworks (e.g., Pytorch, JAX) and compiler tooling (MLIR) for Al/ML application testing
• A strong foundation in Test and Evaluation (T&E) for deep learning software stacks, with a particular emphasis on pre-training and inference of generative workloads
• Experience with system administration and deploying Machine Learning (ML) or High Performance Computing (HPC) workloads in production
• Experience in profiling a diversity of hardware systems such as GPUs, FPGAs, or ASICS for maximizing latency, throughput, and efficiency

EDUCATIONAL REQUIREMENTS:

• Degree Computer Science, Artificial Intelligence, Physics, Applied Mathematics, or related fields. (prefer a Master’s Degree)

• Support and debug Al applications used by internal applied researchers to improve their software workflows for production
• Deploy test plans to profile, optimize, and scale test-time compute to maximize systems for latency, throughput and efficiency performance across a range of Machine Learning (ML) workloads
• Develop validation plans, benchmarks, and test scripts to evaluate stability, performance, and power consumption of hardware systems such as GPU-based HPCs and Al Application Specific Integrated Circuits (ASICS)
• Utilize Deep Learning Frameworks such as PyTorch, JAX, and Tensorflow
• Prototype and analyze emergent techniques in algorithmic and hardware system optimizations
• Implement GPU programming and distributed /parallel computing algorithms
• Interact with internal researchers to help specify benchmarking plans and validation test scripts