Ingénieur en machine learning/Machine Learning Engineer, ProServe Shared Delivery Team - Data & AI at Amazon Web Services Canada, Inc. — NeverHard

Overview The AWS Professional Services (ProServe) team is seeking a skilled Machine Learning Engineer to join as a Delivery Consultant. In this role, you will work closely with customers to design, implement, and manage AI/ML and GenAI solutions on AWS, meeting their technical requirements and business objectives. Key Job Responsibilities Implement end-to-end AI/ML and GenAI projects: understand business needs, prepare data, develop models, deploy and monitor solutions. Design and implement machine learning pipelines that support high‑performance, reliable, scalable, and secure ML workloads. Design scalable ML solutions and MLOps operations using AWS services, leveraging GenAI solutions when applicable. Collaborate with cross‑functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models. Serve as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures. Share knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts. Ensure solutions meet industry standards and support customers in advancing their AI/ML, GenAI, and cloud adoption strategies. This is a customer‑facing role with potential travel to customer sites as needed. Basic Qualifications Experience implementing AWS services in a variety of distributed computing environments. 5+ years of experience in cloud architecture and implementation. 5+ years of experience in data, software, or machine learning engineering, with a strong understanding of distributed computing (e.g., data pipelines, distributed training and inference, ML infrastructure design). 3+ years developing platforms for predictive modeling, natural language processing, and deep learning, with a proven track record of building, hosting, and deploying machine learning models on cloud services (e.g., Amazon SageMaker). 3+ years of development with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficient with industry‑leading ML libraries and frameworks such as TensorFlow and PyTorch. Bilingual in French and English required for candidates located in Quebec. Preferred Qualifications 5+ years of IT implementation experience. Experience and technical expertise in cloud computing technologies. Experience leading the design, development, and deployment of business software at scale or recent hands‑on technology infrastructure, network, compute, storage, and virtualization experience. AWS experience preferred, with proficiency in a wide range of 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 non‑technical 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. Amazon est un employeur garantissant l'égalité des chances et ne fait aucune discrimination sur la base du statut d'ancien combattant protégé, d'un handicap ou de tout autre statut protégé par la loi. #J-18808-Ljbffr