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Montreal Institute for Learning Algorithms

MILA is the machine learning laboratory at the University of Montreal.

Senior Technical Delivery Manager - Sovereign AI Lab

Program ManagementConfirmed live in the last 24 hours
Full-timeMontreal, QC, CanadaIn-person

About the Job

Requirements

  • Five or more years of experience in technical delivery management, technical project or program management, enterprise software implementation, or a comparable customer-facing role.
  • Demonstrated success leading complex software or platform deployments with external enterprise customers or partners, from discovery and planning through validation, operational handoff, and adoption.
  • Experience managing several concurrent deployments, with practical responsibility for scope, milestones, dependencies, risks, stakeholder communication, and acceptance criteria.
  • Technical fluency across enterprise platform delivery, including cloud or on-premises infrastructure, containers, orchestration, networking, security, and operational readiness.
  • Working knowledge of AI systems, including model serving, retrieval, agent orchestration, evaluation, and observability, sufficient to participate in technical discussions and communicate delivery implications.
  • Experience conducting structured customer or user discovery, synthesizing qualitative and operational evidence, and forming clear product recommendations.
  • Ability to build trusted relationships with technical teams and executive sponsors, facilitate difficult decisions, and communicate changes or risks clearly and early.
  • Strong written and verbal communication skills in English and French.
  • A university degree in a field relevant to the role, or equivalent professional experience.

Responsibilities

  • Lead early partner discovery to understand the intended use case, deployment environment, organizational constraints, and success criteria, working with Engineering to assess feasibility before commitments are made.
  • Define and maintain delivery plans across several concurrent partner deployments, including scope, milestones, responsibilities, dependencies, resource needs, risks, and acceptance criteria.
  • Serve as the partner's primary point of accountability during active delivery, communicating progress, decisions, risks, and changes to technical teams and executive sponsors.
  • Act as the primary bridge between the internal team and the deployment partner team throughout the implementation process.
  • Identify delivery risks and unresolved decisions early, assess their implications, and recommend changes to scope, sequencing, timing, or readiness when commitments are no longer credible.
  • Conduct structured feedback sessions with partner administrators and users, translating deployment evidence and feedback into product problems and recommendations.
  • Identify patterns across deployments and develop reusable playbooks, templates, acceptance criteria, and review practices that improve future partner delivery.

Desired Qualifications

  • Delivering open-source products across cloud, on-premises, regulated, security-sensitive, or other customer-controlled environments.
  • Working in professional services, technical consulting, implementation, or another delivery model that includes partner enablement and early adoption.
  • Delivering an early-stage product while its architecture, capabilities, and operating model are still evolving.

About the Company

Montreal Institute for Learning Algorithms

MILA is the machine learning laboratory at the University of Montreal.

Montreal Institute for Learning Algorithms is an artificial intelligence research institute affiliated with Quebec universities. The company conducts machine-learning research, trains students and researchers, publishes scientific work, and collaborates with industry and public organizations. It serves researchers, students, universities, companies, governments, and the broader AI community. Its operating model centers on an academic research community supported by scientific programs, partnerships, computing, and institutional operations. Teams work across machine-learning research, software, education, partnerships, policy, communications, and administration.

Company size
1,001-5,000
Company stage
Grant
Total funding
$5.8M
Headquarters
Montreal, Canada
Founded
1993

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