Badr Larhdir Email & Phone Number

Canada

Marseille, Provence-Alpes-Côte D'Azur, France

Lausanne, Vaud, Suisse

I was in charge of:- Developing robust, production-ready proofs of concept for both Machine Learning Operations (MLOps) & Large Language Models Operations (LLMOps), aimed at optimizing model training and serving/deploying processes.- Investigating the integration of LLMs into Logitech's business operations, including assessing and evaluating infrastructure needs, operational costs, and human resource requirements for implementing LLMs within the existing framework.- Designing and implementing scalable cloud systems on AWS to serve ML and LLMs applications, with a focus on robustness, high availability, and low-latency responses.- Establishing & documenting scalable ML pipelines in collaboration with data scientists, emphasizing DevOps and MLOps practices for efficient deployment, monitoring, and automation within containerized environments.- Developing an API & CLI packager to transform data scientists’ code into executable cloud projects, leveraging GitHub Actions for rapid and seamless deployment, while ensuring the security and reliability of these deployments.Computer Skills:- Cloud Computing: Proficiency in AWS for deploying scalable cloud systems (EC2, Cloudformation & Terraform).- ML and LLM Operations: Knowledge in setting up and managing ML applications and LLMs, including pipeline scalability and efficiency (AWS Sagemaker, S3).- DevOps and MLOps Practices: Expertise in continuous integration and continuous deployment (CI/CD) practices, monitoring (CloudWatch), and automation within containerized environments (Docker).- Programming and Scripting: Experience in developing APIs and CLI tools, involving programming languages such as Python, TypeScript, YAML and Shell scripting.- Security and Reliability: Skills in ensuring the security and reliability of cloud deployments (Amazon IAM & VPC), in containerized environments.- Version Control and CI/CD Tools: Proficient use of GitHub, GitHub Actions, for automating the deployment process.

Lausanne, Vaud, Switzerland

• Designed and developed a web application for rating spatial operators, leveraging React and TailwindCSS for an intuitive user interface, and Node.js with MongoDB for backend services. This project, in collaboration with MIT and the University of Texas Austin, measures and ranks sustainability decisions, aiding in informed decision-making.• Using React, TypeScript, and Express.js, engineered comprehensive end-to-end platform functionality, including dynamic form generation, operator-admin communication, and a sophisticated rating system. Optimized the user experience leading to a 68% reduction in form completion time.• Established a robust Continuous Integration/Continuous Deployment (CI/CD) pipeline using GitHub Actions, enhancing the efficiency and reliability of the deployment process.• Developed RESTful APIs with Node.js and Express.js, ensuring seamless data exchange and integration with the MongoDB database for effective data management and retrieval.• Applied TailwindCSS for responsive and aesthetically pleasing UI design, adhering to modern web standards and enhancing user engagement.• Ensured application security and data protection by implementing JWT for authentication and authorization, along with secure API practices.• Collaborated with cross-functional teams to align the application development with business goals, ensuring that the solution effectively addresses user needs and business objectives.

Bachelor'S Degree, Electrical And Electronics Engineering

Master'S Degree, Electrical, Electronics And Communications Engineering

Electrical and Electronics major in Data and Internet Of Things (IoT).