Ingénieur en machine learning​/Machine Learning Engineer, ProServe Shared Delivery Team - Data

Êtes‑vous enthousiaste à l’idée de créer des solutions logicielles autour de grands systèmes complexes d’apprentissage automatique (AA) et d’intelligence artificielle (IA)? Souhaitez‑vous aider les plus grandes entreprises mondiales à tirer une valeur commerciale de l’adoption et de l’automatisation de l’IA générative (GenIA)? Êtes‑vous motivé à utiliser d’énormes volumes de données hétérogènes pour développer des modèles d’IA/AA? Avez‑vous envie d’apprendre à appliquer l’IA/AA à une grande diversité de cas d’usage en entreprise?

Êtes‑vous enthousiaste à l’idée de jouer un rôle clé chez Amazon, une entreprise qui investit dans l’apprentissage automatique depuis des décennies et qui façonne la technologie mondiale de l’IA?

The Amazon Web Services Professional Services (Pro Serve) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle.

• Experience with AWS services (e.g., Sage Maker, Bedrock, EC2, ECS, EKS, Open Search, Step Functions, VPC, Cloud Formation).
• AWS Professional level certifications (e.g., Solutions Architect Professional, Dev Ops Engineer Professional) preferred.
• Experience with automation and scripting (e.g., Terraform, Python).
• Knowledge of common security and compliance standards (e.g., HIPAA, GDPR).
• Strong communication skills with the ability to explain technical concepts to both technical and non‑technical audiences.
• Experience building ML pipelines with best MLOps practices, including data preprocessing, model hosting, feature selection, hyper‑parameter tuning, distributed training, GPU training, deployment, monitoring, and retraining.
• Experience with MLOps tools (e.g., MLFlow, Kubeflow) and orchestration tools (e.g., Airflow, AWS Step Functions).
• Experience building applications using Generative AI tools and technologies (LLMs, vector stores, orchestrators such as Lang Chain, prompt engineering).
• Experience developing infrastructure as code (e.g., Cloud Formation, CDK, Terraform), containers and CI/CD pipelines.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well‑being.

Salary ranges by location:

• CAN, AB, Calgary – 99,900.00 –  CAD annually
• CAN, BC, Vancouver – 99,900.00 –  CAD annually
• CAN, ON, Toronto – 99,900.00 –  CAD annually
• CAN, QC, Montreal – 99,900.00 –  CAD annually