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TOSAN TECHNO | توسنتکنو

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
Apply by: May 3, 2027
Posting language: English
Posted: Nov 4, 2026

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.

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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

Visa sponsorship

Not detected in the job text

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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