Job Description We are seeking an ML Solutions Architect who brings broad software engineering expertise along with robust 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.

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Key Responsibilities System Integration & Coprocessing: 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.

Technical Consulting: 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 handedoffto our Deep Learning or Reinforcement Learning engineers.

Language-Agnostic Engineering: Build and maintain wrappers, APIs, and microservices that allow our ML stack to remain flexible and language-agnostic across different production environments.

Cross-Functional Coordination: Act as the primary technical liaison between technical leadership, customers, and the core engineering team tospecout data and integration requirements.

Modular Execution: Break down complex product visions into manageable architectural components, ensuring that ML components ship as part of a stable, scalable software product.

Responsabilitsprincipales Intgrationdesystmesetcoprocessing:



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Qualifications Qualifications Education: Degree in Computer Science, Software Engineering, or a related field.

Professional Experience: Proven experience as a Software Architect or Systems Engineer in a fast-paced environment.

Industry Context: Prior experience in industries with complex multi-disciplinary teams such as robotics, smart grids, precision agriculture, game development, or aerospace.

Technical Proficiency: Generalist Tooling: 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#).

Architectural Knowledge: Deep understanding of how to integrate ML models into production software (, API design, message brokers, and containerization, compute and memory budgeting). ML Literacy: While you may not be training models daily, you must have enough ML-adjacent experience to understand model constraints, data requirements, and the ''state of the art.'' Experience with fine-tuning and deploying models is a plus.

Attributes: Strategic Decision-Making: Ability to perform ''Build vs.

Buy'' analyses for ML components.

Communication:



Exceptional ability to translate high-level product vision into concrete engineering specs for both technical leadership and specialized engineers.

Conscientiousness: High attention to detail regarding system stability and interoperability Qualifications Diplmeeninformatique,engnielogicieloudans undomaineconnexe.

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Comptencestechniques Outillagegnraliste: Excellentematrisede Git et desenvironnements

Unix, avec lacapacitdetravaillerdansplusieurslangagesdeprogrammationselonlesbesoins,idalement

Python, C++ouC#.

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Qualitsrecherches Prisededcisionstratgique: Capacitraliserdes analysespertinentesdetypebuild vs. buypour lescomposantsetsystmesintgrantdu ML.

Communication: Excellentecapacittraduireunevisionproduitde hautniveauenspcificationsdingnierieconcrtespour la direction et les quipes techniquesspcialises.

Rigueur: Grande attentionaccorde lastabilitdessystmes, linteroprabilitet lamaintenabilit longterme.

Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal''s policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law.

If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation.

You can submit your request to AccessibilityS.

📌 ML Solutions Architect - Architecte de solutions ML (Montreal)
🏢 NBCUniversal
📍 Montreal