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Chakib B.CB

Chakib B.

AI Engineer - LLM | RAG | AGENTS

€600/day
Paris, FR
8-15 years

Average response time: 1 hour

About Chakib

Experienced Software Engineer and Ph.D. researcher specializing in LLM Agents, RAG systems, and energy-efficient computing. I bridge the gap between cutting-edge AI research and production-ready software. Currently focused on helping businesses deploy custom AI agents and optimizing software infrastructure to reduce operational costs and energy consumption.
  • French

    Native or bilingual

  • English

    Fluent

Can work on-site
Paris (up to 50km), Marseille (up to 50km), Aix-en-Provence (up to 50km), Nice (up to 50km), Cannes (up to 50km)

Experience

  • MCQ-Scan.com
    Lead AI Engineer
    DIGITAL AND IT
    November 2024 - Today (1 year and 7 months)
    Lille, France
    ● Architecture: Architecting high-performance AI agents and optimizing LLM inference for commercial applications.
    ● Performance Optimization: Reduced agent inference latency by 60% and significantly decreased the memory footprint.
    ● Model Fine-tuning: Fine-tuned a 7B parameter model to achieve 95% task accuracy, facilitating a transition away from expensive proprietary APIs.
    ● Reliability: Engineered a constrained decoding pipeline that ensured 100% structured output validity, eliminating downstream parsing errors.
    ● Multimodal Integration: Integrated a custom RAG system (utilizing a proprietary image neural network) to enhance the capabilities of an e-commerce clothing store chatbot.
    artificial intelligence RAG Python Back-End development
  • Qarnot Computing / INRIA
    Software Engineer
    DIGITAL AND IT
    October 2022 - November 2024 (2 years and 1 month)
    Lille, France
    ● Footprint Reduction: Reduced software binary size by 300x (from GBs to MBs), cutting container deployment times by 85%.
    ● Infrastructure Deployment: Deployed PowerAPI across 100+ distinct computing nodes to collect and analyze over 1 million data points regarding software energy efficiency.
    ● Impact: Enabled clients to identify energy leaks, resulting in an estimated 20% average reduction in cloud operational costs for pilot users.
    greenIT Back-End development C++ Python performance optimization
  • Spirals Team, INRIA
    Research Engineer (Green Computing)
    RESEARCH
    February 2018 - October 2022 (4 years and 8 months)
    Lille, France
    ● Tool Adoption: Led the development of pyJoules (92,000+ PyPI downloads) and JouleHunter (3,500+ downloads), both of which are now staple tools in the Green AI research community.
    ● Efficiency Gains: Achieved up to a 30% reduction in energy usage for Python and Java applications without code alterations, saving approximately 150 kWh per year in benchmarked test clusters.
    ● Large-Scale Benchmarking: Managed a massive project covering 40+ programming languages and 780+ framework stacks; generated a dataset used by 50+ international research labs to evaluate language efficiency.
    Python greenIT programming languages software optimization Data analysis

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Education

  • Ph.D.
    University of Lille
    2022
    Ph.D.
  • Engineering & M.Sc. in Computer Science
    Ecole Nationale Supérieure d'Informatique (ESI)
    2017
    Engineering & M.Sc. in Computer Science

Skill set

Categories