Bachiri Nacim
Ile-De-France
Summary
Ingénieur DevOps/MLOps, Motivé et enthousiaste en Cloud et IA, avec 2 ans d’expérience en apprentissage chez STMicroelectronics. Compétences solides en cloud, containerisation, et scripting. Excellentes compétences relationnelles et capacité à optimiser les processus. Passionné par l’intégration de l’IA pour améliorer les performances.
Overview
2
2
years of professional experience
1
1
Certification
Work History
DEV/MLOPS ENGINEER
STMicroelectronics
Paris
09.2023 - 10.2024
- Technical stack: AWS, SQL, Kubernetes, Docker, Python, Jenkins, Ansible, Jira, Git
- Designed and implemented an Infrastructure as Code (IaC) cloud solution on AWS and concertizing the project with AWS CDK and AWS CloudFormation for hosting and deploying machine learning models from ST ModelZoo
- Set up CI/CD pipelines for automated model deployment, including data augmentation, finetuning, and training processes
- Implemented real-time monitoring and visualization using AWS S3, Grafana, and Elasticsearch
- Documented all engineering activities according to established procedures.
ML PLATFORM ENGINEER INTERN
STMicroelectronics
Paris
04.2023 - 09.2023
- Developed MLOps pipelines for deploying deep neural network applications on edge devices
- Development of a solution based on a time-of-flight sensor for deep neural network applications such as gesture recognition/classification or texture recognition
- Containerized ML models using Docker for consistent deployment across different environments
Education
Master of Science - Computer Science
Université Paris-Est Créteil
Paris09-2024
Bachelor of Science - COMPUTER ENGINEERING
INELEC
Boumerdes07-2022
Skills
- AWS
- Python
- SQL & NoSQL
- Grafana
- Elasticsearch
- KAFKA
- Docker
- Ansible
- Kubernetes
- Terraform
- Ml-flow
- CI/CD
- IaC
- Git
- Python
- Java
- C
- C
- AWS SageMaker
- TensorFlow
- Keras
- Pytorch
Projects
- MedAI, Automated Medical Image Analysis Pipeline:
Built a CI/CD pipeline for continuous training and deployment of medical image analysis models and Implemented model monitoring and alerting system for detecting drift and ensuring model reliability. Development of a scalable API for serving ML models in a production environment. The project utilized a deep learning model combining CNNs and Transformers for image analysis and text generation.
- Zero-shot Image Classification with CLIP:
Development of a zero-shot image classification system using OpenAI's CLIP, with finetuning of Open_CLIP models for the CIFAR-100 dataset. The project leverages cosine similarity to enable accurate classification without prior training on target classes, demonstrating high flexibility and adaptability.
Personal Information
Driving License: B
Certification
- Neural Networks and Deep Learning Specialization (Coursera)
- Quantization Fundamentals with Hugging Face (DeepLearning.AI)
- Structuring Machine Learning Projects (Coursera)
- Introduction to Linux (Coursera)
- Programming with Python (Coursera)
Languages
French
Proficient
C2
English
Proficient
C2
Timeline
DEV/MLOPS ENGINEER
STMicroelectronics
09.2023 - 10.2024
ML PLATFORM ENGINEER INTERN
STMicroelectronics
04.2023 - 09.2023
- Neural Networks and Deep Learning Specialization (Coursera)
- Quantization Fundamentals with Hugging Face (DeepLearning.AI)
- Structuring Machine Learning Projects (Coursera)
- Introduction to Linux (Coursera)
- Programming with Python (Coursera)
Master of Science - Computer Science
Université Paris-Est Créteil
Bachelor of Science - COMPUTER ENGINEERING
INELEC