Engineering Manager, Machine Learning Platform

Jobgether· Brussels (Firmensitz, recherchiert)· lever· veröffentlicht 28.07.2026
Muss:DevOpsAISeniorLeadRemote

Accountabilities: The Engineering Manager, Machine Learning Platform will lead a team of platform engineers responsible for developing and operating scalable machine learning infrastructure. This role combines engineering leadership, technical decision-making, roadmap ownership, and cross-functional collaboration to ensure ML systems are reliable, efficient, and aligned with business priorities.

Define and execute the roadmap for machine learning training and serving platforms, including model training systems, deployment workflows, GPU infrastructure, and low-latency serving solutions.

Lead, mentor, and develop a team of platform engineers while remaining engaged in technical strategy and implementation decisions.

Drive execution and operational excellence by balancing reliability, scalability, developer experience, performance, and infrastructure costs.

Build and improve platforms that enable machine learning teams to develop, deploy, and operate models efficiently.

Evaluate and adopt modern machine learning infrastructure technologies, including solutions supporting deep learning, transformer-based workloads, and large-scale compute.

Partner with machine learning engineers, product teams, and infrastructure teams to support critical AI initiatives.

Collaborate with senior engineers on architectural decisions, technical trade-offs, and long-term platform strategy.

Recruit, retain, and grow high-performing engineering talent across different career levels.

Establish best practices that improve platform quality, reliability, and engineering effectiveness.

Requirements:

The ideal candidate is an experienced engineering leader with a strong background in machine learning infrastructure, distributed systems, and team development. You should have demonstrated success building production-grade platforms, guiding technical decisions, and leading teams through complex engineering challenges.

7+ years of experience in software engineering and/or machine learning engineering, including at least 2 years managing engineering teams.

Strong hands-on experience building and operating production machine learning platforms or distributed systems infrastructure.

Experience with one or more areas including ML model training, model serving, deployment workflows, GPU infrastructure, or large-scale compute systems.

Solid understanding of machine learning data requirements, including training datasets, data quality, reproducibility, and evaluation processes.

Familiarity with modern ML technologies such as deep learning, transformer architectures, and large-scale model workloads.

Strong systems thinking and ability to collaborate with senior engineers on complex architectural decisions.

Proven ability to deliver infrastructure platforms that improve engineering productivity and ML team impact.

Experience recruiting, coaching, and developing engineers across multiple experience levels.

Strong communication skills with the ability to collaborate effectively across technical and business teams.

Ability to navigate ambiguity, prioritize effectively, and drive projects from concept through execution.

Experience with applied machine learning modeling is a plus.

Bachelor’s degree in computer science, engineering, or another technical discipline, or equivalent practical experience.

Benefits:

Competitive annual base salary range of $181,000 - $241,000 CAD .

Total compensation package that may include equity rewards.

Comprehensive health coverage with premiums fully covered for employees and dependents.

Flexible spending allowances for technology, food, lifestyle needs, and family-related expenses.

Competitive vacation and holiday schedules to support work-life balance.

Employee stock purchase plan with discounted share purchase opportunities.

Remote-first working environment with flexibility to work from approved locations.

Supportive and inclusive workplace culture focused on employee growth and development.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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