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.
• Evaluate and adopt new technologies like Distributed Ledger or Blockchain.
• Create new solutions to be deployed along existing enterprise software.
• Work as part of team that follows the agile methodology.
• Lead and mentor junior developers who are learning advanced technologies.
• Lead or participate in complex initiatives on selected domains.
• Assure quality, security and compliance for supported systems and applications.
• Serve as a technical resource in finding software solutions.
• Review and evaluate user needs and determine requirements.
• Provide technical support, advice, and consultation with the issues relating to supported applications.
• Create test data and conduct interfaces and unit tests.
• Design, code, test, debug and document programs using Agile development practices.
• Understand and participate to ensure compliance and risk management requirements for supported area are met and work with other stakeholders to implement key risk initiatives.
• Conduct research and resolve problems in relation to processes and recommend solutions and process 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 demonstrated through work experience, training, military experience, education.
• 1 year experience in HPC & Parallel Computing: distributed computing frameworks, multi-threading, and vectorization techniques. Hands-on experience with GPU computing.
• 1 year experience optimizing ML workloads on NVIDIA, AMD, or custom AI Accelerators.
• 1 year experience in Machine Learning Optimization: Frameworks as PyTorch, TensorFlow, JAX. Model paralelization (pipeline and tensor parallelism).
• 1 year Data Processing and I/O optimization experience: Large datasets processing with Parallel I/O. Optimization of memory and data storage.
• 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/and infrastructure.
• Hands-on experience in deploying ML workloads on large-scale HPC clusters.
• M.S./Ph.D. in Computer science or related field is a plus, academic work (theses, research articles, projects, etc.) in the areas of interest mentioned above count as work experience.

Qualifications

• Not explicitly specified beyond experience requirements; formal educational qualifications are implied in the desired qualifications (M.S./Ph.D. preferred).

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