Principal Research Software Engineer
4 weeks ago
We are seeking a highly skilled Principal Research Software Engineer to assist in developing the National Deep Inference Fabric, an open-source deep learning interpretability research computing infrastructure project. The successful candidate will be responsible for full stack development, including back-end and front-end software development, to create a robust, high-throughput, highly usable, and flexible multi-tenant AI inference service. Key responsibilities include solving security, stability, integration, and performance issues involved in providing a large-scale research inference service for open-source AI models. The ideal candidate will have expertise in Python and working internals of PyTorch, as well as Unix/Linux service development, HPC/cloud environments, and all aspects of the software development life cycle.
Responsibilities:
- Design, build, and maintain a high-performance backend compute infrastructure to handle large volumes of traffic and throughput requests from researchers.
- Address software and hardware issues related to security, compliance, privacy, reliability, scalability performance, load testing, and load balancing.
- Independently implement critical components such as scheduling, routing, quota management, authentication, authorization, log analysis, and telemetry for efficient backend operations.
- Lead and actively participate in full-stack web development activities, encompassing both front-end and back-end tasks.
- Implement and manage a robust CI/CD pipeline, following Agile methodology, to facilitate the seamless and efficient deployment of code into production.
- Conduct thorough testing of software to ensure code quality and reliability before promoting changes to the production environment.
- Implement changes, enhancements, and optimizations to ensure a seamless and user-friendly experience for researchers interacting with the platform.
- Apply deep experience in Machine Learning and Large Language Model interpretability research methods to contribute to the ongoing research computing infrastructure project.
- Collaborate with researchers to understand their requirements and integrate different open-source machine learning models into the platform effectively.
- Stay abreast of advancements in the field of machine learning, interpretability research, and PyTorch to ensure the platform aligns with the latest industry standards and practices.
Qualifications:
- Six plus years of experience as a Staff Full-Stack Software Engineer or Research/Staff Scientist.
- Master's degree (or more) in artificial intelligence, computer science, or equivalent.
- Knowledge of Machine Learning methods, including Transformer Language Models.
- Excellent software development skills, including expertise with PyTorch & Python internals.
- Strong written and verbal communication team-player who can think and work independently.
Documents to Submit:
CV and cover letter
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