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    Lead Software Engineer - Geneva, Schweiz - CERN

    CERN
    CERN Geneva, Schweiz

    Gefunden in: Talent CH C2 - vor 5 Tagen

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    Contract
    Beschreibung

    Job Description

    Introduction

  • Leading the development and managing the maintenance of hls4ml () and Conifer (), two software libraries developed by CERN and its partners to deploy machine learning algorithms on FPGAs.
  • Leading the development of a library for hardware-aware end-to-end training and optimization of neural networks, supporting compression techniques such as pruning and quantization and interfaced to hls4ml.

    • Functions

    As the coordinator of these two activities, you will:

  • Supervise and recruit a team of computer scientists to work on software development and contribute directly to the design and implementation of the required ML libraries.
  • Ensure the timely achievement of the NGT milestones related to both tasks (e.g., software release, documentation, presentations at conferences).
  • Work in close contact with experts from the LHC experiments and external partners within the FastML ( ) community. This partnership aims to identify user requirements and strategize their implementations.
  • Organize periodic user-community workshops to communicate on the status of the tasks and gather information on additional requirements and functionalities.
  • Participate in managing common activities of the NGT project alongside other task leaders.

    • Qualifications

    Master's degree or PhD or equivalent relevant experience in the field of Experimental Particle Physics or Computing Science or a related field.

    Experience:

    You have:

  • Demonstrated experience in high-performance software development including task prioritization, and customer interaction;
  • Demonstrated experience with FPGA programming with knowledge of High Level Synthesis libraries (Vivado, Quartus, etc..);
  • Proven mastering of performance and memory profiling technologies and debugging techniques for both CPU and GPU programming;
  • Knowledge of distributed training techniques for machine learning algorithms;
  • Expertise in neural network compression techniques such as pruning, quantization, etc;
  • Proven track record of scientific publications;
  • Experience in managing software development projects in scientific environments will be considered as a valuable experience;
  • Understanding of machine learning applications for High Energy Physics will be considered an advantage.

    • Technical competencies:

  • Knowledge of programming techniques and languages
  • Development of application software
  • Knowledge and application of software life-cycle tools and procedures: machine learning training software (PyTorch, Tensorflow, Horovod).
  • Testing, diagnosing and optimization of software
  • Conceptualising, designing and developing user experiences and interfaces

    • Behavioural competencies:

  • Achieving Results: having a structured and organised approach towards work; being able to set priorities and plan tasks with results in mind. Delivering prompt and efficient service taking into account customer needs.
  • Solving Problems: recognizing what is essential; discriminating between important and peripheral information and being able to see the whole picture. Being open to original ideas and creative options by which to address issues; continually driving change by seeking new ways to improve outcomes.
  • Learning and Sharing Knowledge: sharing knowledge and expertise freely and willingly with others; coaching others to ensure knowledge transfer.
  • Demonstrating Flexibility: adapting quickly and resourcefully to shifting priorities and requirements.
  • Communicating Effectively: delivering presentations in a structured and clear way; adjusting style and content to the audience; responding calmly and confidently to questions.

    • Language skills:

    Spoken and written English: ability to understand and speak the language in professional contexts. Ability to draw-up technical specifications and/or scientific reports and to make oral presentations. The willingness to learn French language would be an asset.

    Additional Information

    Eligibility and closing date:

    has been an integral part of CERN's mission since its foundation and is an established value of the Organization. Employing a diverse workforce is central to our success. We welcome applications from all .

    This vacancy will be filled as soon as possible, and applications should normally reach us no later than

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