Machine Learning Engineer Job at XL Scientific, LLC , Albuquerque, NM

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  • XL Scientific, LLC
  • Albuquerque, NM

Job Description

Verus Research is searching for a Machine Learning Engineer to perform research & development, conception, and implementation of advanced concepts in artificial intelligence, machine learning, autonomous systems, and mobile robotics. The ideal candidate should have experience developing and implementing machine learning algorithms with a focus on some combination of generative methods, data fusion, classification, verification and validation, optimization, computer vision, and/or reinforcement learning.

The primary role for the Machine Learning Engineer will be to aid in the conception and development of machine learning algorithms and training pipelines supporting data-driven outcomes relevant to automated, intelligent, autonomous systems. This work will require the ability to work both independently and within a team. A successful team member will be able to work on diverse application areas with an initial focus on advancing state of the art in spacecraft autonomy.

The ideal candidate for the Machine Learning Engineer position will possess strong analytical skills used to solve challenging problems in a fast-paced environment. In addition, they will possess the following:

  • U.S. Citizen
  • Advanced degree (M.S. or Ph.D.) in computer science, mathematics, statistics, aerospace engineering, electrical engineering, or related fields
  • 3+ years of experience working on machine learning problems
  • Strong background in stochastic processes, statistical inference, optimal control theory
  • Knowledge of deep learning architectures such as CNNs, RNNs, and NLP, and time series analysis
  • Demonstrated experience working on deep learning pipelines including familiarity with data processing, model selection, training, validation, testing, PyTorch, TensorFlow, or other machine learning frameworks
  • Proficient in Python, R and C++
  • Ability to communicate technical concepts clearly and concisely, both verbally and in writing
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