• Apply software engineering skills, design skills, and creative thinking to build cutting edge AI systems.
  • Identify and refine project requirements, solutions to potentially abstract AI challenges, and well-defined performance metrics.
  • Design and develop software as scalable architectures, components, API’s and systems.
  • Translate project requirements into executable roadmaps for creating and measuring technical capability.
  • Work in high intensity, joint teams of software engineers and research scientists.
  • Designing, developing and maintaining core system features, services and engines.
  • Helping define product features, drive the system architecture, and spearhead the best practices that enable a quality product.
  • Working with scientists and other engineers to investigate design approaches, prototype new technology, and evaluate technical feasibility.
  • Operating in an Agile/Scrum environment to deliver high quality software against aggressive schedules.


  • Expert level python programmer who have had experience designing and rolling a large scale resource navigator based projects: Kubernetes or AWS Lambda.
  • At least 5 years of experience coding and debugging in one or more general purpose programming languages including, but not limited to: Java, C/C++.
  • Ability to transfer project requirements into robust software components and architectures.
  • Experience with standard machine learning techniques and frameworks.
  • Experience analyzing large scale data from a variety of sources.
  • Design, validation, and characterization of algorithms and/or systems.
  • Academic and/or industry experience with standard AI and ML techniques, NLU and scientific thinking.
  • Experience with machine learning tools and frameworks including but not limited to: TensorFlow, PyTorch, Torch, Caffe, etc.
  • Experience developing cloud software services and an understanding of design for scalability, performance and reliability.
  • Experience defining system architectures and exploring technical feasibility trade-offs.
  • Experience optimizing for short term execution while planning for long term technical capabilities.
  • Ability to prototype and evaluate applications and interaction methodologies.
  • Ability to produce code that is fault-tolerant, efficient, and maintainable.
  • Experience working effectively with science, data processing, and software engineering teams.
  • Written and verbal technical communication skills with an ability to present complex technical information in a clear and concise manner to a variety of audiences.


  • Graduate degree (MS or PhD) in Electrical Engineering, Computer Sciences, Mathematics, or related technical field.

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