Research Scientist - Deep Learning for Computer Vision & Image Analytics

Job Description

We are seeking hands-on, full-time, Research Scientists and Staff Research Scientists with deep knowledge and interest in Deep Learning for Computer Vision and Image Analytics and with a focus on their extensions and industrial application. Our research group works with Siemens’ business units from the early phase of finding opportunities through designing solutions and implementing prototypes as well as government funding agencies to develop cutting edge application prototypes and end solutions. We need someone who thinks creatively, is innovative, and curious to find sound solutions to customer problems to help us transform industry!

This right person for this role has extensive knowledge and experience in research, design, and implementation of algorithms in Deep Learning for Computer Vision and Image Analytics as well as competencies in building applications in Augmented and Virtual Reality. The person will also have the ability to apply image and video analysis techniques to large-scale, real-world problems.

The Challenge

In this role as a Research Scientist, you will:

  • Research, design, and implement algorithms in Deep Learning for Computer Vision and Image Analytics.
  • Contribute to research projects that develop a variety of algorithms and systems in computer vision, image and video analysis.
  • Advance the state-of-the-art in the field, including generating patents and publications in top journals and conferences.
  • Apply image and video analysis techniques such as deep learning to large-scale, real-world problems.
  • Fast prototyping, feasibility studies, specification and implementation of image and video analysis product components.
  • Working with customers to understand algorithm requirements and deliver high-quality solutions.

The Candidate

  • Ph.D. in Computer Science, Electrical Engineering, or related discipline required. Strong background in Deep Learning.
  • Research Scientists will have a min of 3 years of Graduate research and internship experience in Computer Vision, Machine Learning and Image Understanding preferred. Staff Research Scientists will have a min of 6 years of experience in fields mentioned.
  • Proven track record developing new research ideas as demonstrated by a strong publication record and early developments to the level of a working system prototype.
  • Strong theoretical and practical background in computer vision, image and video analysis, specifically object detection, tracking and recognition, statistical modeling, statistical pattern recognition, machine learning, sparse methods, applied mathematics, optimization.
  • Hands-on coding skills and ability to quickly prototype in C++ is a must. Further experience in Scripting languages such as Python is a plus.
  • Practical experience and proficiency with Machine Learning modeling frameworks such as PyTorch, TensorFlow, etc.
  • Strong understanding of data-efficient learning techniques
  • Experience building analytics applications using Machine or Deep Learning for the deployment on edge devices.
  • Experience with CAD models, and sensor generated data such as point cloud data.
  • Experience in training algorithms with limited data, specifically semi-supervised/weakly supervised training techniques, experience with deep generative models
  • Outstanding written and verbal communication skills in English are required.
  • Excellent interpersonal skills and a can-do attitude.
  • Ability to work independently and prioritize work.
  • Strong collaboration skills and ability to thrive in a fast-paced environment.
  • Flexibility and adaptability to work in a diverse and dynamic team.
  • This position requires employees to be fully vaccinated against COVID-19 unless they are granted a medical or religious exemption

Successful candidate must be able to work with controlled technology in accordance with US Export Control Law. US Export Control laws and applicable regulations govern the distribution of strategically important technology, services and information to foreign nationals and foreign countries. Siemens may require candidates under consideration for employment opportunities to submit information regarding citizenship status to allow the organization to comply with specific US Export Control laws and regulations. Additional information on the US Export Control laws & regulations can be found on

About Us

Siemens Technology employees are passionate about applied research. We create technology with purpose that benefits society - more agile and productive factories, more intelligent and efficient buildings and grids, more reliable and sustainable transportation. Our work powers Siemens products and is regularly featured in patents and publications. We operate in a global ecosystem focused on innovation, partnering with our customers, businesses, government agencies, and leading academic institutions on highly visible projects where collaboration is key.

Our people continuously develop their talents, are curious, and are not afraid to take risks in pursuit of technological innovation. A strong learning culture empowers employees at Siemens Technology to own their growth and development.

We know that diversity fuels innovation and drives business success. We are committed to creating an inclusive environment, where diversity of thought, culture, and experience is seen as our greatest strength. This is what brings our best ideas to life.

We take pride in bringing our best selves to work every day, prioritizing individual health, work-life blend, and flexibility.

At Siemens Technology, the success of our employees drives our success.


Organization: Technology

Company: Siemens Corporation

Experience Level: Experienced Professional

Job Type: Full-time

Equal Employment Opportunity Statement
Siemens is an Equal Opportunity and Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law.

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