Machine Learning Engineer / Scientist

Introduction

ARA Rocky Mountain Division is seeking a Machine Learning Engineer or scientist to join a growing, elite, interdisciplinary team supporting multiple R&D projects for Defense and National Security customers. Strong candidates will have a solid background in using machine learning techniques to address complex problems. Examples of the sorts of problems you’ll be involved with include automated imagery and video analytics, autonomous systems, medical decision support, behavioral modeling and forecasting, and natural language processing. This position will be based in San Antonio, TX with the potential for occasional travel. Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information.

What you’ll do as a Machine Learning Engineer/Scientist

• Serve as our expert in machine learning, often interacting with partners and customers as part of a dispersed team to develop and test ML applications for various National Defense and Homeland Security applications.
• Build prototype and production-ready data processing and machine learning pipelines.
• Lead the development of state-of-the-art machine learning systems and help lead the transition of these technologies to our customers.
• Help to expand our team and maintain ARA’s competitive edge by contributing to business growth initiatives on topics of your choosing.
• Work independently as well as collaboratively with teams supporting AI and machine learning research in wide-ranging domains such as autonomous systems, cyber and electronic warfare, aerial/ground/naval/space platforms, biotechnology, medical applications, and more.
• Engage in collaborative brainstorming and problem solving to define requirements, lay out objectives, explore potential solutions, and inform strategy and architecture design.
• Develop, test, and deploy software in an agile, continuous integration/continuous delivery environment.
• Recommend tools and capabilities to ARA, our partners, and our customers as part of a continuous effort to embrace and leverage emerging technologies.
• Seamlessly mesh tech know-how with business acumen to help us navigate all our cloud computing needs, including infrastructure design, maintenance, support, and planning, and everything in between.
• Help to expand our team and maintain ARA’s competitive edge by contributing to business growth initiatives on topics of your choosing.
• Occasionally travel to the DC area for collaboration with customers and partners.

Machine Learning Engineer/Scientist Requirements

• US Citizenship and eligibility to apply for and hold a US security clearance.
• BS or higher in computer science, engineering, applied mathematics, or a closely related field OR any of the following certifications:
  • AWS Certified Machine Learning - Specialty
  • AWS Certified Data Engineer - Associate
  • Certified Kubernetes Administrator (CKA)
  • NVIDIA-Certified Associate AI Infrastructure and Operations (NCA-AIIO)
  • Microsoft Certified: Azure AI Fundamentals
  • Microsoft Certified: Azure AI Engineer Associate
• 5+ years of relevant work experience applying machine learning techniques.
• Strong software architecture and development skills, with some experience in applying a variety of machine learning techniques.
• Proven track record in all stages of the product development life cycle, from requirements definition through system design, development, and deployment.
• Thorough understanding of classical and modern machine learning theory and practical experience implementing approaches in deep learning and neural networks, planning and optimization, inference methods, statistics, and information theory.
• Experience programming in at least one or more of the following and their ML related libraries or frameworks:
  • Python (Numpy, Pandas, Matplotlib, Seaborn, sci-kit Learn),
  • Java (Weka, JavaML, ELKI),
  • C++ (TensorFlow, Torch, mlpack),
  • R (xgboost, mlr, PARTY, CARET),
  • Javascript (Brain.js, Tensorflow.js, machinelearn.js)
• Experience programming using frameworks such as TensorFlow, Spark+MLib, SageMaker, Keras, MXNet, Gluon, PyTorch, Keras, SciKit-Learn.
• Familiar with the following development tools:
  • Git
  • GitLab
  • MLFlow
  • JupyterLab/GoogleColab
• Ability to present your designs and sell your solutions to various stakeholders.

Machine Learning Engineer/Scientist Preferences

• GitHub or Kaggle with full projects and associated documentation or contributions to open-source projec