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6-12 Month Internship - AI/CV Intern

Job Description

We are seeking 1-2 graduate interns to join our Sustainable Automation Solutions Research Group in Princeton, NJ for 6-12 months. Our team is responsible for a variety of exciting projects in Digitalization and Sustainability with Siemens customers throughout the aerospace and automotive industries, and we need your help! 

The Challenge 

In the role as a AI/CV Intern, you will:

  • Work under the direction and guidance of a principal investigator to develop and enhance Siemens’ offering for Industrial Automation 
  • Contribute into developing AI/CV based solutions, apps and algorithms, with the purpose of automation through Artificial Intelligence in industrial applications including agriculture and manufacturing. (Simply put, use CV to automate the manual processes in agriculture, or manufacturing)
  • Research & implement CV/ML methods across computer vision applications such as image segmentation, object detection, image classification, as well as other machine learning domains (time-series analytics, and anomaly detection applications)
  • Strengthen your mastery over standard & cutting-edge CV and ML tools and packages (opencv, tensorflow/pytorch, sklearn, etc.)
  • Work with a team of experts in industrial automation, AI, intelligent manufacturing, and control to understand customer challenges and produce innovative solutions
  • Design, implement, test, validate, and document software components and algorithms, and build apps for industrial edge devices
  • Apply cutting edge research findings and technologies to address industry challenges in applications of AI in Automation and Digitalization 
  • Gain expertise using state of the art software development technologies and learn best practices of modern programming (e.g., git, docker, CI/CD)
  • Gain familiarity with state-of-the-art industrial automation and control technologies (e.g., Siemens Industrial Edge)

The Candidate 

Qualified candidates will have: 

  • Active enrollment as a PhD or MSc Student in Computer Science, Electrical Engineering, Mechanical Engineering, Operations Research, or a related discipline
  • Experience in developing and implementing computer vision algorithms/solutions in two or more areas of image segmentation, object detection, image classification, knowledge and extraction of popular image features, image registration
  • Experience in implementing classical computer vision and ML methods as well as some deep learning 
  • Experience in pytorch/tensorflow, and in at least one of the packages of opencv, sklearn, or other image processing packages
  • 2+ years of programming experience in object-oriented languages like Python or C++, with at least 1+ year of Python programming experience
  • Familiarity with Linux, and some knowledge/experience of git and docker is preferred.
  • In summary, an applicant with graduate-level knowledge and implementation skills of computer vision and machine learning fundamentals and algorithms, for example, a student who has completed two or more graduate courses in Computer Vision and/or Deep Learning, and has completed the corresponding high-level projects using Python, can be a qualified applicant.
  • A passion for real-world problem solving and a can-do attitude
  • Excellent interpersonal and communication (verbal & written) skills
  • Curiosity to ask questions and find innovative solutions to technical challenges
  • Where permitted by applicable law, Siemens may require employees to be fully vaccinated against COVID-19 based on job requirements, and in accordance with an accommodation based on legally protected reasons

May consider sponsorship of short-term J-1 visa students (6-12 months), dependent upon program requirements 

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 https://www.bis.doc.gov/index.php/policy-guidance/deemed-exports/deemed-exports-faqs 

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: Student (Not Yet Graduated)

Job Type: Full-time



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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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