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Developer – Large Audio Language Models (LALMs) & End-to-End Speech-to-Speech Systems

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
Posted

Original job description

We are seeking a highly skilled and motivated AI Engineer to design, develop, and deploy advanced solutions using Large Audio Language Models (LALMs) and end-to-end Speech-to-Speech (S2S) systems. This role focuses on building real-world, production-ready applications that integrate speech recognition, language understanding, and speech synthesis into seamless voice-driven experiences.

You will work at the intersection of AI, deep learning, and speech technologies, contributing to innovative products rather than purely theoretical research.

Key Responsibilities
  • Design and implement end-to-end speech-to-speech systems integrating ASR, LLMs, and TTS components
  • Develop and optimize Large Language Models (LLMs) and Large Audio Language Models (LALMs) for real-world applications
  • Build scalable pipelines for speech and language data processing, including data collection, augmentation, and preprocessing
  • Fine-tune models on domain-specific datasets to improve performance and contextual accuracy
  • Evaluate and benchmark voice agents using modern frameworks and real-world conversational data
  • Apply prompt engineering techniques to enhance model responses and system behavior
  • Integrate AI models into backend systems and deploy them in cloud environments
  • Collaborate with cross-functional teams (product, engineering, and research) to deliver production-grade solutions
  • Continuously optimize models for latency, scalability, and quality (speech intelligibility and language accuracy)
Required Qualifications
  • Master’s or PhD (or equivalent experience) in Computer Engineering, Artificial Intelligence.Strong programming skills in Python.
  • Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch
  • Solid understanding of neural networks and deep learning techniques for speech and language processing
  • Expertise in Large Language Models (LLMs), speech recognition (ASR), and text-to-speech (TTS) systems
  • Experience with end-to-end speech-to-speech architectures and multimodal AI systems
  • Knowledge of prompt engineering and model fine-tuning techniques
  • Familiarity with tools and frameworks such as LangChain, LangGraph, or similar orchestration tools
  • Experience with backend systems, APIs, databases, and containerization (e.g., Docker)
Preferred Skills
  • Experience with evaluation frameworks for voice agents (e.g., EVA or similar tools)
  • Strong understanding of model evaluation metrics for speech quality, accuracy, and contextual relevance
  • Experience handling large-scale datasets and building efficient data pipelines
  • Knowledge of speech data augmentation techniques
  • Ability to rapidly learn and apply emerging AI technologies
Core Competencies
  • Strong problem-solving and optimization skills
  • Hands-on, product-focused mindset with a passion for building real-world AI solutions
  • Attention to detail, with a structured and methodical approach to development and documentation
  • Strong communication and collaboration skills across technical and non-technical teams
  • Ability to work independently while contributing effectively in a team environment
Why Join Us?

This is a unique opportunity to work at the forefront of AI innovation, shaping the future of speech-to-speech systems and intelligent voice applications. You will play a key role in building next-generation AI products that have real-world impact.

More about this job

Responsibilities

Design, build, and optimize production-ready speech-to-speech systems that combine speech recognition, language models, and speech synthesis, including data pipelines, domain-specific fine-tuning, and voice-agent evaluation. Integrate and deploy models in backend and cloud environments, collaborating across teams while improving latency, scalability, speech intelligibility, and language accuracy.

Requirements

Requires a master's degree, PhD, or equivalent experience in Computer Engineering or Artificial Intelligence, strong Python skills, and hands-on experience with TensorFlow or PyTorch. Candidates should have expertise in LLMs, ASR, TTS, end-to-end speech-to-speech and multimodal systems, model fine-tuning and prompt engineering, and familiarity with orchestration tools and backend technologies.

Skills

  • Python
  • PyTorch
  • TensorFlow
  • Large Language Models
  • Large Audio Language Models
  • Speech Recognition
  • Text-to-Speech
  • Speech-to-Speech Systems
  • Deep Learning
  • Prompt Engineering
  • Model Fine-Tuning
  • Multimodal AI
  • LangChain
  • LangGraph
  • Docker
  • Speech Data Processing

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Categories

  • Technology
  • Software
  • Engineering
  • Data & Analytics
  • Science & Research

Keywords

  • Python
  • TensorFlow
  • PyTorch
  • Large Language Models
  • Large Audio Language Models
  • Speech-to-Speech Systems
  • Automatic Speech Recognition
  • Text-to-Speech
  • Deep Learning
  • Neural Networks
  • Multimodal AI
  • Prompt Engineering
  • Model Fine-Tuning
  • LangChain
  • LangGraph
  • Backend Systems
  • APIs
  • Databases
  • Docker
  • Cloud Deployment
  • Speech Data Processing
  • Data Augmentation
  • Voice-Agent Evaluation
  • Speech Quality Metrics
  • Model Optimization
  • Computer Engineering
  • Artificial Intelligence
  • Conversational Data
  • Speech Synthesis
  • Language Understanding

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