Numerical Computing Researcher / Expert - AI Infrastructure

Eu Recruit
Paris, France
1 month ago

Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Paris, France

Tech stack

Artificial Intelligence
C++
Python
Parallel Computing
TensorFlow
Scientific Computating
Software Engineering
PyTorch
Numerical Computing
Information Technology

Job description

Our client in Paris is seeking a highly skilled Numerical Computing Specialist to join their cutting-edge AI Infrastructure team. You will be part of a world-class R&D group dedicated to developing next-generation infrastructure for large-scale AI models. In this role, you will address core numerical computing challenges to enable efficient, accurate, and scalable model training and inference. They welcome candidates at multiple levels, including exceptional recent PhD graduates and seasoned technical experts., * Conduct advanced research in numerical computing for large model training and inference

  • Design and implement innovative techniques, such as:
  • Sparse matrix computation
  • Low-rank approximation and tensor decomposition
  • Mixed precision computation and stability analysis
  • Quantization and dimensionality reduction
  • Collaborate closely with system, compiler, and parallel computing experts to integrate innovations into real-world systems
  • Publish in top-tier conferences or contribute to impactful industrial solutions

Requirements

  • Strong background in numerical linear algebra, scientific computing, or applied mathematics
  • Proven ability to implement and analyze algorithms involving matrix/tensor computation
  • Strong coding skills in Python and/or C++, with experience using AI frameworks such as PyTorch, TensorFlow, or JAX
  • Ability to read and write academic papers; fluent English

Preferred:

  • PhD in computer science, applied mathematics, or related field (or equivalent industry experience)
  • Research experience in one or more of the following:
  • Sparse/dense matrix algorithms
  • Mixed precision or adaptive precision methods
  • Model compression or efficient representation
  • Experience with AI compilers, numerical kernels (e.g., cuBLAS, CUTLASS), or HPC libraries
  • Publications in leading conferences such as NeurIPS, ICML, ICLR, SC, SIAM, etc.

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