Advanced Technology Senior Software Engineer

About the Role

Key Responsibilities

• Design, develop, and optimize HPC solutions for large-scale ML workloads.
• Optimize data pipelines for high-throughput model training (Dask, Ray, NVIDIA RAPIDS).
• Profile, optimize, and accelerate deep learning models on GPUs, TPUs, and multi-node clusters.
• Work on low-level performance tuning - vectorization, memory optimization.
• Develop and benchmark custom kernels for AI models using CUDA, ROCm, OpenACC, OpenMM.
• Implement distributed training strategies using MPI, DeepSpeed, PyTorch/XLA.
• Collaborate with ML researchers and engineers to deploy scalable ML models.
• Research and implement new HPC techniques.
• Create new solutions to be deployed along existing enterprise software.
• Lead and mentor junior developers who are learning advanced technologies.
• Assure quality, security, and compliance for supported systems and applications.
• Review and evaluate user needs and determine requirements.
• Provide technical support, advice, and consultation related to supported applications.
• Create test data and conduct interfaces and unit tests.
• Design, code, test, debug, and document programs using Agile development practices.
• Participate in ensuring compliance and risk management requirements are met.
• Conduct research and resolve process-related problems, recommending improvements.
• Assist other individuals in advanced software development.
• Collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals.

Requirements

• 4+ years of Specialty Software Engineering experience or equivalent through work, training, military experience, or education.
• 1 year experience in HPC & Parallel Computing: distributed frameworks, multi-threading, vectorization, with hands-on GPU computing experience.
• 1 year experience optimizing ML workloads on NVIDIA, AMD, or custom AI Accelerators.
• 1 year experience in Machine Learning Optimization with frameworks like PyTorch, TensorFlow, JAX, including model parallelization.
• 1 year experience in Data Processing and I/O optimization for large datasets, including memory and storage optimization.
• 1 year experience with Cluster HPC, HPC schedulers, and familiarity with cloud-based HPC (AWS Parallel Cluster, Azure ML, Google Cloud TPUs).

Nice to Have

• 1+ years of experience in HPC, ML optimization, or infrastructure.
• Hands-on experience deploying ML workloads on large-scale HPC clusters.
• M.S./Ph.D. in Computer Science or related field, or academic work in relevant areas.

Qualifications

• Educational background in Computer Science or related field (preferred but not mandatory).

Benefits & Perks

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement