Machine Learning Engineers work with Research Engineers and Software Engineers on diverse projects including: developing cutting edge algorithms and prototype applications, providing software design and programming support to research projects in the domain of deep learning, robotics and self-driving cars. They are the bridge between basic research and implementation, transferring our theoretical results into real world. And by real world, we mean smart robots.

At Ascent we are creating a passionate and engaging culture, combining the best of academia and product-led environments, providing a balance of structure and flexibility. Our approach encourages collaboration across all groups within the Research and Engineering teams, leading to creativity and innovative breakthroughs at the forefront of robotic research. As a Research Engineer, you'll have option to work on different fields and will be able to do a mix of research and engineering tasks.

Responsibilities

  • Provide software design and programming support to research projects
  • Report and present software development including status and results clearly and efficiently both internally and externally, verbally and in writing
  • Participate in research, internal R&D
  • Implement, evaluate and report on algorithms, research papers and studies

Requirements

Minimum Qualifications

  • BS/BEng degree in computer science, mathematics, physics, electrical engineering, machine learning or equivalent
  • Experienced in C/C++
  • Experienced in at least one scripting language such as Lua, Python or Matlab and a desire to learn new programming languages
  • Familiarity with software collaboration tools (git, Jira, etc.)
  • Experience with implementing numerical methods and data visualization
  • Good knowledge of algorithm design and ability to interpret research papers
  • Hands-on experience with modern machine learning software and tools (such as Tensorflow, Caffe, Kubernetes, Docker, Chainer, Ansible, Logstash, etc.)
  • Hands-on experience with cloud or computational infrastructure (such as high-end Nvidia devices, Amazon AWS, Google Cloud, etc.)

Plus points for any of the following

  • Master's degree in a technical field
  • Experience with GPU Programming (CUDA, OpenCL)
  • Experience in working on production systems, software products, webservices or embedded systems
  • Interest in neuroscience and robotics
  • Published papers or conference talks in relevant fields
  • Passion for AI
  • Contributions to open source projects

Benefits

Self-development support, expenses for trips to AI events and gym membership will be provided as benefits.