Senior Engineer Foundation Models
3 months ago
Our team has an immediate permanent opening for a Senior Engineer.
Responsibilities:
- Research, prototype and build core infrastructure, tooling, and platforms to improve the productivity, quality, and efficiency of engineering and serving foundation model applications.
- Design, implement and assess application programming APIs, frameworks and runtime systems software for heterogeneous architectures (e.g., GPU, NPU), familiar with machine learning systems or AI infrastructures.
- Support the integration process of novel software frameworks on in-house hardware platforms (e.g. performance modeling, analysis of future computing architectures, resource allocation and management, scheduling, fault tolerance and resiliency, communication and shared memory).
- Meet top industry and academic leaders and experts around the world, collaborate with top researchers and students, consult with Engineering teams across diverse domains, publish research papers in far-reaching and impactful areas, and submit patent applications for novel inventions.
What you’ll bring to the team:
- Master or PhD Degree in Computer Science, Electrical & Computer Engineering, Machine Learning, or relevant domains.
- Solid experience with one or more of the following programming languages: Python/C/C++/Go; Familiarity with software development practices (version management, build management, CI/CD, debugging and profiling).
- Solid understanding in any of these areas: Machine Learning and/or Deep Learning, Large Models Training and Finetuning (e.g., NLP/CV)
- Experience with mainstream model training and inference frameworks and tools (e.g., PyTorch, Tensorflow, PaddlePaddle, Oneflow, MindSpore, HuggingFace Transformer&Accelerate, DeepSpeed, Megatron, FasterTransformer, Triton Inference).
- Solid understanding in Computer Architecture, Distributed Computing, Parallel Computing, Cloud Native, Operating Systems, Networks; experience in using frameworks and tools of any of the aforementioned areas (e.g., Spark, Flink, Ray for Distributed Computing, Docker, K8S for Cloud-Native app/framework development).
- Ability to evaluate, apply, and mature published research to real-world problems on prototype systems.
- Have an inquisitive mindset, proven research and communication skills, can conduct investigations and experiments independently, and can interpret experiment data and present results clearly and concisely.
- Publications in related top-tier venues (e.g., ICSE, FSE, TSE, ICLR, ICML, NeurIPS, OSDI, SOSP) is an asset.
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