Principal AI Solutions Software Engineer, AI Systems (UK - Remote)

Working at SambaNova

SambaNova Systems is hiring a Principal AI Solutions Software Engineer, AI Systems. This role offers an unparalleled opportunity to work E2E (end-to-end) with cross-functional teams across Sambanova's software, hardware and ML teams to transform cutting-edge AI research into customer-empowering solutions with superior AI System performance and accuracy, propelling us towards making a substantial impact across diverse industries. We eagerly welcome individuals with exceptional talent to join us in this transformative journey.

Responsibilities 

• Work with both external users and internal engineering teams to develop robust, efficient and scalable AI solutions that meet customers' needs.
• Integrate the latest model architecture, data curation, and performance optimization technologies from the AI industry and research into SambaNova's technical stack.
• Create end-to-end solutions for ML applications to enable model training and fine-tuning on domain-specific data.
• Enable high throughput and low latency inference applications for at-scale deployment.
• Collaborate with cross-functional software and hardware teams to innovate customer-centric applications.
• Work with diverse data types: textual, unstructured, tabular and multimodal data.

Basic Qualifications

• Bachelor's or higher degree in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or Statistics
• 5+ years of industry experience, including 3+ in one or more of the following: 
  • Deep learning algorithm development
  • Compiler
  • Software-Hardware Co-design
• Proficiency in Python or C++, with a solid foundation in data structures, algorithms, and machine learning.
• Proficiency in one or more of the popular ML frameworks (PyTorch/Tensorflow/JAX)

Additional Required Qualifications

• Experience in machine learning productization and pipeline development in software engineering
• Real-world experience in multi-lingual LLM applications training and inference.
• Real-world experience in vision-language multimodality.
• Development and deployment Model Training and Inference at scale, Synthetic Data, Information Retrieval, Machine reading comprehension, RLHF/RLAIF, Question Answering, Copilot.
• Development with DeepSeed, Megatron, vLLM, and TensorRT.

Preferred Qualifications

• CUDA/OpenCL programming skills. Experience with CuDNN, and CUDA math libraries (CuBLAS, CuFFT,..) is a plus.
• First author in CS/ML publication

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