Member of Technical Staff, Multimodal Infrastructure

• Design, develop and maintain large-scale multimodal data processing pipelines
• Design, develop and maintain large-scale multimodal model pretraining and post-training frameworks
• Design, develop and maintain large-scale multimodal model inference and serving frameworks
• Work with research scientists and product engineers to solve infra-related problems
• Find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively
• Enjoy working in a fast-paced, design-driven, product development cycle
• Embody our Culture and Values

• Bachelor's Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
• Experience in multi-modal data processing: Strong proficiency in distributed data processing infra (resource utilization management, fault tolerance, ray & spark) and CPU/GPU batch processing optimizations
• Experience with state-of-art model inference and serving frameworks
• Experience with image/video/audio data processing
• Experience with common data formats for efficient I/O
• Experience in multi-modal pretraining and post-training: Strong proficiency in deep learning frameworks such as PyTorch, Megatron and Deepspeed
• Knowledge of auto-regressive and diffusion transformer models
• Experience with distributed training techniques such as data parallelism, model parallelism, and pipeline parallelism
• Proven experiences in at least one of the following areas: image/video generation and editing
• efficient architectures (e.g., MoE, window attention)
• efficient model design
• or reinforcement learning training methods (e.g., RLHF, DPO, GRPO)
• Experience in multi-modal inference and serving: Strong proficiency in serving frameworks such as vLLM, TensorRT-LLM, SGLang, xDiT, Cache-DiT etc.
• Knowledge of distillation techniques such as Progressive Distillation, DMD, Self forcing etc.
• Knowledge of quantization and compression techniques like AWQ, GPTQ, and FP8 for multi-modal pipelines
• Experience in distributed inference scaling across multi-node clusters using Ray Serve and Triton
• Experience in leading technical projects and supporting architectural decisions with data

Bachelor's Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience