Duration: 12-Month Contract (Potential Extension)Work Model: Hybrid (Downtown Toronto - 3 days in office)Engagement Model: Professional Services Engagement – B2 B (Incorporated Consultants Preferred)About the Engagement Akkodis is partnering with a leading institutional investment and pension organization to engage an experienced Senior AI Platform Engineer (MLOps) to support the ongoing growth and operationalization of enterprise AI capabilities.This is a highly technical, hands-on engineering role focused on building, deploying, governing, and operating machine learning and AI platforms at enterprise scale. The successful candidate will work closely with AI Governance, Cybersecurity, Enterprise Architecture, Platform Engineering, and AI Centre of Excellence teams to implement responsible AI controls, operationalize machine learning models, and establish scalable AI deployment standards.While the role supports AI governance and responsible AI initiatives, the primary focus is technical implementation. The client is seeking a strong engineering professional with deep MLOps, machine learning operationalization, cloud engineering, and Python development experience who can translate governance requirements into automated controls, deployment processes, and platform capabilities.This chance is ideal for someone who enjoys solving complex technical problems, building enterprise-grade AI capabilities, and working across infrastructure, machine learning, security, and platform engineering domains.Services to be Provided Design, build, and maintain enterprise MLOps and LLMOps capabilities supporting AI and machine learning solutionsDevelop and automate model deployment, monitoring, evaluation, governance, and lifecycle management processesBuild CI/CD pipelines and Infrastructure as Code solutions supporting AI and machine learning environmentsImplement model governance, auditability,



approval workflows, and operational controls within production AI platformsSupport implementation of responsible AI and AI governance requirements through technical controls and automationDevelop and maintain model tracking, lineage, experiment management, and reproducibility capabilitiesImplement and enhance MLflow, Databricks, evaluation frameworks, and related platform servicesCollaborate with Cybersecurity, Enterprise Architecture, and AI Governance teams to operationalize enterprise requirementsBuild and support AI deployment patterns for machine learning, RAG, and generative AI solutionsTroubleshoot, debug, and resolve platform, deployment, performance, and operational issuesCreate technical documentation, implementation standards, operational procedures, and support guidesSupport platform reliability, observability, monitoring, incident management, and recovery processesImplement cloud cost monitoring, optimization, and consumption management practicesProvide technical guidance and enablement to teams adopting enterprise AI capabilitiesCommunicate technical solutions and implementation outcomes to both technical and senior business stakeholders5+ years of experience in MLOps, Machine Learning Engineering, AI Platform Engineering, Cloud Engineering, or related technical disciplinesProven experience operationalizing machine learning models in enterprise production environmentsExperience designing and supporting model lifecycle management, deployment, monitoring,



and governance processesStrong understanding of MLOps best practices, CI/CD, automation, testing, and software engineering principlesExperience with Databricks, MLflow, or comparable machine learning platform technologiesExperience working with cloud platforms such as Azure, AWS, or Google CloudExperience with Infrastructure as Code methodologies and toolingHands-on experience with Terraform and modern deployment automation practicesExperience with Git Hub Actions, Jenkins, Azure Dev Ops, or similar CI/CD technologiesExperience troubleshooting complex distributed systems and production environmentsStrong understanding of machine learning model operationalization, evaluation, and observabilityExperience implementing secure deployment and access control patterns within cloud or AI environmentsExcellent communication skills with the ability to engage both technical and non-technical stakeholdersProven ability to operate independently and deliver within fast-paced and evolving environmentsImportant This is a business-to-business engagement. Candidates must represent an incorporated entity, hold a valid business number, maintain appropriate insurance, and invoice for services rendered.We thank all applicants for their interest in this opportunity. Only candidates meeting the above qualifications will be contacted for further discussions.Accessibility At Akkodis, part of The Adecco Group, our purpose is simple: to make the future work for everyone. We live our values, Passion, Collaboration, Inclusion, Courage, and Customers at Heart, by fostering a workplace where diversity is celebrated and every voice matters. We encourage applications from individuals of all backgrounds and identities. Together, we’re making the future work for everyone.#J-18808-Ljbffr

📌 Senior Ai Platform Engineer (Mlops) (Toronto)
🏢 Akkodis
📍 Toronto