Senior ML/DL Developer

-English to follow-

About Stay22

Based in Montreal, Stay22 helps ambitious creators and digital platforms with strong intent turn their existing traffic into incremental revenue, with technology that works quietly in the background.

Today, more than 6,500 creators and platforms rely on Stay22, with over $1 billion in annual transactions flowing through the platform. Originally built for travel, the company now supports partners across retail, lifestyle, publishing, events, and transportation, as it continues to expand its monetization infrastructure for the modern creator economy.

You will join the Neuro Squad, a specialized team created to centralize ML and AI innovation at Stay22. Neuro provides the technical foundations that power our core engines, including Roam (our machine learning-driven redirection engine).

As a Senior ML/DL Developer in the Neuro Squad, you will be responsible for designing and architecting the intelligence behind these products. This role is not just about building models - it is about taking ownership of the entire lifecycle of our ML platforms - from designing training pipelines to optimizing real-time inference APIs.

You will work with cutting-edge technologies (including LLMs) and collaborate closely with the Data Team and Forge Squad to ensure our AI solutions are scalable, secure, and production-ready.

Key Responsibilities

Machine Learning and Product Logic

• Take ownership of the backend logic and model behavior for Roam, ensuring high accuracy and reliability.
• Continuously improve models for ranking quality, latency, and revenue efficiency using advanced statistical analysis and deep learning.
• Develop high-performance models for forecasting and user intent prediction based on complex tabular and booking data.

AI Infrastructure & MLOps

• Design and maintain the internal LLM client and gateway layers, enabling unified access to language models for the entire organization.
• Design and operate the full ML lifecycle: data preparation, training pipelines, model registries, and real-time inference services.
• Manage caching layers, inference servers, and performance monitoring to ensure low latency for our high-traffic engines.
• Deploy robust, maintainable, and production-ready solutions aligned with CI/CD and security standards (in collaboration with the Forge Squad).

Collaboration and Mentorship

• Collaborate with the Data Squad to co-design training datasets and feature pipelines, ensuring seamless integration with the data warehouse and analytical systems.
• Expose ML capabilities as robust APIs and services, allowing aligned squads (e.g., Hub, EmbedX) to integrate them easily without managing ML complexity.
• Act as a mentor and technical advisor, supporting teams in prototyping ML features and adopting best practices in AI.

Education and Experience

• Proficiency in English required for daily communications with international colleagues and partners.
• Master's degree (M. Sc.) in computer science, machine learning, data mining, statistics, or a related technical field.
• 6+ years of experience in machine learning or data science.
• Minimum of 2 years of software engineering experience, including writing production-ready backend code or APIs.
• Machine learning and deep learning
• Excellent proficiency in Python and deep learning libraries such as PyTorch or TensorFlow, as well as scikit-learn.
• Strong understanding of modern ML techniques, including CNNs, LSTM/RNN, and gradient boosting models (XGBoost, LightGBM) applied to tabular data.
• Demonstrated ability to implement and optimize LLMs, including Transformers, custom embeddings, and LLM gateway or client creation.

MLOps and Real-Time Systems

• Experience with Google Vertex AI (preferred) or Amazon SageMaker for training and managing large-scale models.
• Strong experience in designing real-time inference and API systems (beyond batch processing).
• Experience with MLOps tools (e.g., MLflow, Kubeflow, TFX) and containerization (Docker, Kubernetes).
• Excellent SQL skills and experience collaborating on feature stores or ETL definitions.

Human Skills and Mindset

• Ability to design reusable, robust, and easy-to-consume systems for other teams.
• Strong interest in translating complex ML metrics into tangible business value (better redirection, higher conversion rates).
• Desire to stay at the forefront of AI infrastructure and modeling techniques.
• What to Expect in Our Hiring Process
• We know your time is valuable - here are the key steps in the process:
• Preliminary call with our talent acquisition partner (30 to 45 minutes)
• Whiteboarding session on Miro with the engineering team (60 minutes)
• In-person interview with some members of the Neuro Squad (45 to 60 minutes)
• Final interview with our CEO (30 minutes)
• Offer and Onboarding
• *Note that this process may be modified at any time based on team needs.*

Why Join Stay22?

• Support travel creators: Contribute to a mission that enables creators to travel more through passive revenue growth.
• Propel your growth: We hire ambitious people and give them the space to excel, grow quickly, and develop their strengths.
• Make a real impact: Our teams are encouraged to take initiative and influence Stay22's future.
• Prime location: Enjoy our bright and dynamic offices in the heart of Little Italy, surrounded by cafes, restaurants, and shops.
• Be yourself: Casual dress code and flexible work hours.
• Comprehensive benefits: Health and dental insurance, retirement plan, training and development opportunities, social activities, and team retreats.

*(Stay22 is an equal opportunity employer. All qualified candidates will be considered. If you have a disability or special need requiring accommodations, please contact us at careers@stay22.com.)* -

About Stay22

Based in Montreal, Stay22 helps ambitious creators and intent-rich digital platforms turn their existing traffic into incremental revenue, with technology that works quietly in the background.

Today, more than 6,500 creators and platforms rely on Stay22, with over $1 billion in annual transactions flowing through the platform. Originally built for travel, the company now supports partners across retail, lifestyle, publishing, events, and transportation, as it continues to expand its monetization infrastructure for the modern creator economy.

You will join the Neuro Squad, a specialized team created to centralize ML/AI innovation at Stay22. Neuro provides the technical foundations that power our core engines, including Roam (our ML-driven redirection engine).

As a Senior ML/DL Developer in the Neuro Squad, you will architect the intelligence behind these products. This role is not just about building models - it is about owning the end-to-end lifecycle of our ML platforms - from designing training pipelines to optimizing real-time inference APIs. You will leverage cutting-edge technologies (including LLMs) and collaborate with the Data Team and Forge Squad to ensure our AI solutions are scalable, secure, and production-ready.

Key Responsibilities

Core ML & Product Logic

• Own the backend logic and model behavior for Roam, ensuring high accuracy and reliability.
• Continuously refine models for ranking quality, latency, and revenue efficiency using advanced statistical analysis and deep learning.
• Develop high-performance models for forecasting and user intent prediction based on complex tabular and booking data.

AI Infrastructure & MLOps

• Build and maintain the internal LLM client and gateway layers, enabling unified access to language models for the entire organization.
• Design and operate the full ML lifecycle: data preparation, training pipelines, model registries, and real-time inference services.
• Manage caching layers, inference servers, and performance monitoring to ensure low latency for our high-traffic engines.
• Deploy robust, maintainable, and production-ready solutions aligned with CI/CD and security standards (in collaboration with the Forge Squad).

Collaboration and Mentorship

• Collaborate with the Data Squad to co-design training datasets and feature pipelines, ensuring seamless integration with the data warehouse and analytical systems.
• Expose ML capabilities as robust APIs and services, allowing aligned squads (e.g., Hub, EmbedX) to integrate them easily without managing ML complexity.
• Act as a mentor and technical advisor, supporting teams in prototyping ML features and adopting best practices in AI.