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What you’ll be doing:
Architect and lead development of next-generation Deep Learning and multimedia algorithms for processing of speech and audio applications.
Train Speech Enhancement models, assess them for quality, performance, and finetune them.
Analyze model accuracy and bias and recommend the next course of action & Improvements.
Improve processes for speech data processing, augmentation, filtering & training sets preparation.
Optimize algorithms for optimal performance on the GPU tensor cores
Collaborate with various teams to drive an end to end workflow from data curation and training to performance optimization and deployment
Influence strategic decisions in the team and product roadmap
Partner with system software engineers and validation teams to build and ship production-quality code.
What we need to see:
PH.D./MS in Computer Science or a closely related engineering field with 3+ years of relevant experience
Strong background in Deep Learning including model design, pruning & performance optimization, transfer learning etc
4+ years of experience of leading cross-module projects and taking them to productization
Strong software engineering background with proficiency in C or C++
Hands-on expertise with PyTorch, TensorRT, CuDNN and one or more Deep Learning frameworks (Tensorflow, Keras etc)
Familiarity/expertizewith various cloud frameworks e.g. AWS, GCP, Azure is a big plus
CUDA programming experience is a plus
Excellent communication and collaboration skills
Self-motivated and able to find creative practical solutions to problems
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