bechir@terminal:~

$ cat resume.txt

Bechir Braham - Software Engineer

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Personal Information

Bechir Braham profile picture
Name:Bechir Braham
Email: bechir.braham@outlook.com
Phone:(+49) 15510031681
Location:Munich, Germany
LinkedIn: bechir--braham
GitHub: Bechir-Braham

Professional Summary

Software Engineer specializing in scalable DevOps pipelines, distributed systems, and machine learning infrastructure.

Work Experience

Software Engineer

Fernride - Build Automation and Tooling Team
  • • Managed and maintained a Bazel-based build system for autonomous and teleoperated terminal trucks, supporting a multi-language monorepo.
  • • Operated and contributed to CI (Continuous Integration) infrastructure across on-premises, AWS and Azure cloud environments; Utilized Terraform for infrastructure as code, integrated microservices with Kubernetes, and implemented robust monitoring, alerting, and SLOs (Service Level Objectives).
  • • Designed and led the implementation of a static analysis gating solution to enforce safety certification requirements (TÜV), reducing static analysis violations from ~10,000 to ~200 in six months.
  • • Designed a hibernation based solution for CI cloud machines to preserve the Bazel server cache, potentially resulting in over 90% performance improvement for cold job runs and approximately 60% reduction in compute costs.
  • • Integrated recorded real-world vehicle-simulation tests into CI as a safety-quality gate, sped up runtime using multi-level caching (shared Lustre Filesystem + Bazel remote cache), and added the checks to PR and merge pipelines to speed impact analysis for certified releases.

Software Engineering Intern

Paul Scherrer Institut - Detectors Group
  • • Architected and implemented a data analysis library for hybrid pixel X-ray detectors using C++. The library is able to read and write data from different file formats, send and receive data from multiple servers, synchronize between data-streams and analyze data using different optimized algorithms.
  • • Developed Python bindings with pybind11 to expose C++ internals, enabling users to write readable and easy to use Python code while benefiting from C++ performance.
  • • Provided an easy to use parallelization framework for scientists to run their algorithms. Users are able to run algorithms on: multiple threads, multiple processes and multiple distributed nodes communicating via ZeroMQ.
  • • Improved the parallelization of Python threads (4x improvement) by releasing and acquiring the Global Interpreter Lock (GIL) carefully in the Python bindings.

Software Engineering Intern

Paul Scherrer Institut - Detectors Group
  • • Contributed to the development of an open-source GUI application for testing and configuring hybrid X-ray detectors. The interface was developed using Python and PyQt and it binds to C++ code for faster backend communication with the detector server.
  • • Implemented unit, integration, and end-to-end testing, reaching test coverage of over 80% for the GUI application.
  • • Automated C++ code generation for the SLS detector package's command-line interface using Python, reducing code complexity and significantly improving maintainability and flexibility.

DevOps & Backend Engineer (Working Student)

Upkurs
  • • Established CI/CD (Continuous Integration and Deployment) pipelines for both development and production environments on Google Cloud (GCP); managed deployments for Cloud Storage, MongoDB databases, and mail services.
  • • Implemented a NestJS service that communicates with Google Calendar API using OAuth 2.0 to generate Google Meet links and return them to clients over WebSockets.
  • • Improved backend servers' response times for Authentication and User services by up to 70% through asynchronous programming and algorithmic optimizations.

Machine Learning R&D Intern

Laboratory of Images, Signals and Intelligent Systems, University Paris-Est Créteil
  • • Performed comprehensive literature reviews and critically evaluated machine learning methodologies for PTSD recognition using EEG (electroencephalogram) data.
  • • Co-authored review paper, contributing analytical insights and actionable recommendations for advancing EEG-based PTSD detection approaches.

Deep Learning & Computer Vision Engineer Intern

EZZAYRA
  • • Managed a team of 4 interns to design, test and deploy a deep learning model on an agricultural autonomous robot to locate and classify ripe and unripe strawberries.
  • • Achieved an mAP (mean average precision) of 0.82 using a YOLO based model and deployed the model with web interface as a prototype.

Technical Skills

Programming Languages

PythonC++JavaScriptGoJava

DevOps

CI/CDBazelGitHub ActionsDockerKubernetesAnsibleTerraformGitLinux

Cloud Computing

AWSAzureGCP

Machine Learning/AI

PyTorchTensorFlowRay

Education

Software Engineering Diploma (Equivalent to Master of Science)

National Institute of Applied Science and Technology (INSAT), University of Carthage
  • Located in Tunisia
  • Comprehensive software engineering curriculum
  • Master's level education with focus on practical applications

Certifications

  • Fundamentals of Accelerated Computing with CUDA C/C++
    NVIDIA Deep Learning Institute (DLI)
    March 2023
  • Fundamentals of Accelerated Computing with CUDA Python
    NVIDIA Deep Learning Institute (DLI)
    July 2022
  • Building Intelligent Recommender Systems
    NVIDIA Deep Learning Institute (DLI)
    June 2022
  • Fundamentals of Deep Learning
    NVIDIA Deep Learning Institute (DLI)
    May 2022
  • TensorFlow: Advanced Techniques
    Coursera
    March 2022

Publications

Machine Learning-based Approaches for Post-Traumatic Stress Disorder Diagnosis using Video and EEG Sensors: A Review

Alice Othmani, Bechir Brahem, Younes Haddou and Mustaqueem Khan

IEEE Sensors Journal, 2023 (Q1, Impact factor: 4.3)

journal - 2023

iCompass at WANLP 2022 Shared Task: ARBERT and MARBERT for Multilabel Propaganda Classification of Arabic Tweets

Taboubi Bilel, Bechir Brahem, and Hatem Haddad

Empirical Methods in Natural Language Processing (EMNLP) Workshops 2022 (Class A*)

conference - 2022

Language Skills

Arabic: Native, English: Proficient (C1), French: Good (B2), German: Basic (B1) and enrolled in a B2 course.