Deep Learning Speech Researcher
About the company
We’re taking Generative Voice AI to a new level. Creatives of all kinds rely on Resemble’s immersive voice engine to rapidly accelerate the development of new voice-centric experiences without losing the flexibility and humanness of speech.
Resemble AI supercharges your synthetic voice with a text-to-speech generator paired with real-time APIs to build immersive experiences. Use cases include, advertisements, games, virtual assistants, call centers and more.
About the role
As a Deep Learning Researcher, you will play a vital role in our research and development efforts. You will be part of a dynamic team focused on pushing the boundaries of voice technology, leveraging PyTorch and other cutting-edge tools. This position offers exciting opportunities to make a significant impact and contribute to groundbreaking advancements in the field. What you'll do
This is an individual contributor role with significant impact both within the machine learning team and on the product team(s) you will collaborate with
You will be responsible for technical roadmaps and will collaborate with Product Management, Data Science, Product Engineering, and Design to shape the overall product roadmap
You will conceive and lead projects while being a hands-on builder of machine learning software components
You will be a strategic thought partner for leaders across the organization on driving business impact through machine learning
You will coach and mentor the next generation of strong engineers on the team
Conduct cutting-edge research in deep learning techniques for voice AI, with a focus on GANs, LLMs, and Diffusion Modelling.
Design and implement state-of-the-art deep learning models using PyTorch, with a specific emphasis on voice synthesis and manipulation.
Collaborate closely with cross-functional teams to develop innovative solutions and enhance our voice-centric products.
Stay up-to-date with the latest advancements in deep learning, voice AI, and related fields, integrating them into our research and development processes.
Analyze and interpret data to derive meaningful insights and optimize the performance of voice models.
Author research papers and actively participate in relevant conferences and workshops.
Strong expertise in deep learning techniques, including GANs, LLMs, and Diffusion Modelling.
Extensive hands-on experience in developing and training deep learning models using PyTorch.
Solid understanding of machine learning fundamentals, including neural networks, recurrent neural networks (RNNs), and convolutional neural networks (CNNs).
Proficient in Python programming and familiarity with relevant libraries and frameworks.
Strong problem-solving and analytical skills.
Excellent communication and collaboration abilities.
Degree in computer science, engineering, or a related field, with a focus on deep learning or voice AI.
Demonstrated expertise in natural language processing (NLP) and voice synthesis.
Familiarity with other deep learning frameworks (e.g., TensorFlow, Keras).
Published research papers or active participation in conferences and workshops related to voice AI and deep learning.
Experience with cloud computing platforms and distributed systems.