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Machine Learning Engineer

Position Description:

The Computational Science Initiative (CSI) at Brookhaven National Laboratory (BNL) invites exceptional candidates to apply for a research engineer position in emerging technology and scientific computing. This position offers a unique opportunity to develop scientific software for emerging technology and high-performance computing (HPC) with applications in diverse scientific domains of interest to BNL and the Department of Energy (DOE). Topics of specific interest include: (i) developing novel distributed / federated machine learning algorithms, (ii) secure computing including blockchain, (ii) improving communication framework (i.e. edge or HPC), and (iii) implementing analytical algorithms to improve DOE applications on edge, HPC, or quantum computer. The position includes access to world-class HPC and quantum computer resources, such as the BNL Institutional Cluster, IBM Q and DOE leadership computing facilities. Access to these platforms will allow computing at scale and will ensure that the successful candidate will have the necessary resources to solve challenging DOE problems of interest.

Essential Duties and Responsibilities:

  • Develop scientific software for emerging technology and high-performance computing (HPC)
  • Implement ML algorithms for scientific applications.
  • Work in interdisciplinary collaborations with applied domain scientists on various aspects of scientific data generation, processing, and analysis.

Required Knowledge, Skills, and Abilities:

  • Bachelor's or higher-level degree in computer science, electrical engineering, or a related field, and 3+ years relevant experience
  • Software developing skill
  • Experience in implementing machine learning algorithms on machine learning platforms (i.e. PyTorch, TensorFlow, JAX, DeepSpeed, etc)

Preferred Knowledge, Skills, and Abilities:

  • Blockchain
  • Edge computing
  • Quantum computing in both hardware and simulation (PennyLane, cuQuantum, Cirq, Qiskit, Tensorflow Quantum, etc)
  • Experience in developing quantum machine learning algorithms
  • Experience in parallel and distributed computing / training
  • Message-oriented middleware