Ingénieur en machine learning/Machine Learning Engineer, ProServe Shared Delivery Team - Data &[...]

Amazon Web Services Professional Services is seeking a skilled Machine Learning Engineer to join our Delivery Consultant team. Key Responsibilities

Implement end‑to‑end AI/ML and GenAI projects, from business requirement gathering to data preparation, model development, deployment, and monitoring. Design and implement machine learning pipelines that support high‑performance, reliable, scalable, and secure workloads on AWS. Architect scalable ML solutions and MLOps workflows using AWS services, leveraging GenAI tools when applicable. Collaborate with cross‑functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to operationalize data and AI/ML models. Provide trusted advisory to customers on AI/ML and GenAI solutions and cloud architectures, offering strategic guidance. Share knowledge and best practices within the organization through mentoring, training, publishing, and creating reusable artifacts. Ensure solutions meet industry standards and support customers in advancing their AI/ML, GenAI, and cloud adoption strategies. Lead the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout projects. Travel to client sites as required for project delivery. Basic Qualifications

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 proven experience deploying models on cloud services such as Amazon SageMaker. 3+ years of development experience with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficiency with industry‑leading ML libraries and frameworks such as TensorFlow and PyTorch. Bilingual in French and English required if the candidate is located in Quebec. Preferred Qualifications

5+ years of IT implementation experience, including cloud computing technologies. Experience designing, developing, and deploying business software at scale, with hands‑on experience in infrastructure, networking, compute, storage, and virtualization. Proficiency in a wide range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation). Professional AWS certifications such as Solutions Architect Professional or DevOps Engineer Professional. Experience with automation and scripting (e.g., Terraform, Python). Knowledge of common security and compliance standards (e.g., HIPAA, GDPR). Strong communication skills, capable of explaining technical concepts to both technical and non‑technical audiences. Experience building ML pipelines with MLOps best 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 developing applications using Generative AI technologies (LLMs, vector stores, orchestration engines such as LangChain, Prompt Engineering). Experience developing Infrastructure as Code (e.g., CloudFormation, CDK, Terraform), containers, and CI/CD pipelines. We encourage candidates who meet many but not all of these preferred qualifications to apply. Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or any other legally protected status. Our culture embracing diversity and inclusion enables our teams to deliver the best results for our customers.

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