{"id":4313065,"url":"https://alion.io/job/quantum-mlops-developer","title":"MLOps Developer","company":{"id":1050427,"name":"Quantum","domain":"quantum.ca","url":"https://alion.io/company/quantum-ca","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":155000,"max":null,"currency":"CAD","period":"year","gross":null,"usd_annual":108674},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"DVC","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-11-13T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-11-13T00:00:00Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Position: MLOps DeveloperLocation: Toronto, 2 days onsite (12 minutes by car from Union Station)Salary: Up to $155KPosting Type: Open vacancyWe are seeking an experienced MLOps / Machine Learning Platform Engineer to design, develop, and maintain end-to-end automation across the AI/ML lifecycle within a GCP cloud environment. This role will focus on building and optimizing ML infrastructure, developing CI/CD pipelines for machine learning models, and automating data processing, model training, deployment, and serving.What you will do:- Own End-to-End Automation.- Develop automated tools for all stages of the AI/ML pipeline in a cloud environment, spanning data processing, model training, and serving.- Design and maintain CI/CD pipelines tailored for ML artifacts (data, models, and code).- Work with DevOps team to provision, manage, and scale cloud-based infrastructure (primarily GCP) to support high-throughput inference.- Optimize deep learning models for seamless deployment and performance across web and mobile platforms.- Collaborate closely with ML engineers and product teams to convert domain-specific APIs into structured, LLM-controllable tools.- Conduct peer code reviews, automated testing, and promote agile methodology.Requirements:- 3+ years of hands-on experience as a MLOps \"developer\" in a an IaC (Infrastructure as Cloud) development environment- Strong automation and programming skills in Python to develop automation tools and workflows- Experience with GCP cloud (MUST-HAVE), NOT AWS and NOT Azure- Experience with Data Version Control Tools (DVC) such as MLFlow- Experience with Docker container orchestration and Kubernetes- Solid ML fundamentals: understanding how models are trained, versioned and deployed- End-to-end ML pipeline ownership, including maintenance, reliability and cost optimization- Strong engineering practices and familiarity with modern tooling- Education: Education in a technical fieldIdeal Candidate Profile:- Someone from a startup or mid-sized organization who has worked across infrastructure, ML pipelines and deployment, rather than a narrowly specialized engineer from a large MLOps team.Interested? Please send your updated resume to Cristina Arsene at .\nREFER A NEW HIRE AND EARN A CASH BONUS! For details, click here.\nAll applications are reviewed by our recruitment team, and hiring decisions are made by people. 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