Senior Speech Applied Scientist

Description

At Omilia, we are revolutionizing the world of customer service through Conversational AI. We believe in creating natural, human-like interactions between people and technology. Our team is at the forefront of innovation, pushing the boundaries of what's possible in speech and language understanding. We are looking for a brilliant and passionate Senior Speech Applied Scientist to join our core team and build the future of voice-based conversational experiences.

The Role

Are you passionate about building the next generation of conversational AI?

The Senior Speech Applied Scientist will be a vital part of our core speech-to-speech (s2s) team, responsible for designing and developing the groundbreaking S2S LLM architecture that will power Omilia's future products. You will have a direct and significant impact on our customers in complex environments like drive-through ordering and enterprise customer service.

You will conduct cutting-edge research and development on an S2S LLM architecture with full-duplex capabilities, aimed at delivering the most natural and seamless conversational experiences in the industry.

What You'll Do:

• Pioneer Research:
   Research and implement state-of-the-art approaches for multi-modal LLMs within an end-to-end, speech-to-speech dialog system architecture.
• Train & Optimize:
   Drive the training, fine-tuning, and optimization of our multi-modal LLMs. Your focus will be on enabling full-duplex conversational capabilities, advanced tool-calling, robust barge-in detection, stronger reasoning, in-context learning, and context-aware natural speech generation.
• Build Data Flywheels:
   Design and implement robust data pipelines for the entire multi-modal LLM lifecycle, including data curation, preparation, model training, and rigorous evaluation.
• Scale Our Infrastructure:
   Develop and optimize our training infrastructure to enable fast, large-scale experimentation (multi-GPU and multi-node training), dramatically accelerating our S2S model development cycle.
• Collaborate & Deploy:
   Work closely with product and engineering teams to transform your research models into robust, scalable, and deployable services that our customers will love.
• Publish Your Work:
   Publish pioneering research at top-tier academic conferences while successfully deploying systems into production environments.

Requirements

• A PhD or MSc in Computer Science, Electrical Engineering, Computational Linguistics, or a related field with a focus on speech processing or deep learning.
• Proven experience in one or more of the following areas: Automatic Speech Recognition (ASR), Text-to-Speech (TTS), Natural Language Processing (NLP), and Spoken Language Understanding (SLU).
• Deep hands-on experience with deep learning frameworks like PyTorch, TensorFlow, DeepSpeed or Lightning.
• Strong background in training, fine-tuning, and evaluating Large Language Models (LLMs), especially in multi-modal or speech-related contexts.
• Experience with large-scale model training on distributed, multi-GPU/multi-node infrastructure.
• A strong publication record in top-tier conferences (e.g., ICASSP, Interspeech, NeurIPS, ACL) is a plus.
• A proactive, collaborative, and innovative mindset with a passion for solving challenging problems.

Benefirts

• Fixed compensation;
• Long-term employment with the working days vacation;
• Development in professional growth (courses, training, etc);
• Being part of successful cutting-edge technology products that are making a global impact in the service industry;
• Proficient and fun-to-work-with colleagues;
• Apple gear.

Omilia is proud to be an equal opportunity employer and is dedicated to fostering a diverse and inclusive workplace. We believe that embracing diversity in all its forms enriches our workplace and drives our collective success. We are committed to creating an environment where everyone feels welcomed, valued, and empowered to contribute their unique perspectives without regard to factors such as race, color, religion, gender, gender identity or expression, sexual orientation, national origin, heredity, disability, age, or veteran status, all eligible candidates will be given consideration for employment.