Job description 

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/expertize with 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