Job Title

tesvous enthousiaste lide de crer des solutions logicielles autour de grands systmes complexes dapprentissage automatique (AA) et dintelligence artificielle (IA)? Souhaitezvous aider les plus grandes entreprises mondiales tirer une valeur commerciale de ladoption et de lautomatisation de lIA gnrative (GenIA)? tesvous motiv utiliser dnormes volumes de donnes htrognes pour dvelopper des modles dIA/AA? Avezvous envie dapprendre appliquer lIA/AA une grande diversit de cas dusage en entreprise? tesvous enthousiaste lide de jouer un rle cl chez Amazon, une entreprise qui investit dans lapprentissage automatique depuis des dcennies et qui faonne la technologie mondiale de lIA? The Amazon Web Services Professional Services (ProServe) 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. Key job responsibilities Implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring. Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads. Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable. Collaborating with crossfunctional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models. Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures. Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts. Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies. Preferred Qualifications Experience with AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation). AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps 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 nontechnical audiences. Experience building ML pipelines with best MLOps practices, including data preprocessing, model hosting, feature selection, hyperparameter 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 LangChain, prompt engineering). Experience developing infrastructure as code (e.g., CloudFormation, 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 signon 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 wellbeing. Salary ranges by location: CAN, AB, Calgary 99,900.00 166,900.00 CAD annually CAN, BC, Vancouver 99,900.00 166,900.00 CAD annually CAN, ON, Toronto 99,900.00 166,900.00 CAD annually CAN, QC, Montreal 99,900.00 166,900.00 CAD annually #J-18808-Ljbffr