ML Solutions Architect - Architecte de solutions ML

NBCUniversal • Montreal, QC

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About The Position

We are seeking an ML Solutions Architect who brings broad software engineering expertise along with strong machine learning-adjacent experience. In this role, you will lead the high-level design of systems that integrate ML models into our broader product suite. You will act as a technical consultant, evaluating customer requirements and determining whether they can be addressed with off-the-shelf solutions or should be escalated as specialized research initiatives for our Deep Learning and Reinforcement Learning teams. This role is ideal for a systems-minded engineer who can translate product vision into scalable architecture, while balancing technical feasibility, performance, and maintainability.

Requirements

• Degree in Computer Science, Software Engineering, or a related field.
• Proven experience as a Software Architect or Systems Engineer in a fast-paced environment.
• Prior experience in industries with complex multi-disciplinary teams such as robotics, smart grids, precision agriculture, game development, or aerospace.
• Fluency with Git, and the Unix shell, with a strong ability to work across multiple programming languages as needed (ideally including one or more of Python, C++, C#).
• Deep understanding of how to integrate ML models into production software (e.g., API design, message brokers, and containerization, compute and memory budgeting).
• Sufficient ML-adjacent experience to understand model constraints, data requirements, and the "state of the art."

Nice To Haves

• Experience with fine-tuning and deploying models is a plus.
• Experience in industries with complex multi-disciplinary teams such as robotics, smart grids, precision agriculture, game development, or aerospace.

Responsibilities

• Design and implement the software layers that allow ML models to interact with a real-time rendering engine. This includes managing data pre-processing and post-processing (coprocessing) to ensure high-performance execution.
• Evaluate incoming customer requirements to determine the optimal path forward. You will decide if a task can be solved using off-the-shelf tools or if it requires a deep-dive research project to be handed off to our Deep Learning or Reinforcement Learning engineers.
• Build and maintain wrappers, APIs, and microservices that allow our ML stack to remain flexible and language-agnostic across different production environments.
• Act as the primary technical liaison between technical leadership, customers, and the core engineering team to spec out data and integration requirements.
• Break down complex product visions into manageable architectural components, ensuring that ML components ship as part of a stable, scalable software product.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior