Computer Vision Researcher

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Hiring Remotely in United Kingdom
Remote
Artificial Intelligence • Logistics • Transportation
The Role

About Us: 

Terminal builds software that digitises, indexes, and automates the yard, leveraging best-in-class machine learning. Our platform will provide warehouse operators with the intelligence needed to optimise their usage of trucks, trailers, chassis, containers and personnel. These are the fundamental operating assets of commerce - and represent the last great frontier of untapped data. In the process, Terminal will address many industry-wide pain points, including compliance, manual processes, equipment location, phantom costs, and labour inefficiencies. Ultimately, Terminal will become the central nervous system for the yard, seamlessly connecting all data sources to support an extensive range of essential functions. 

 

Overview: 

Our world class vision engineering team has built an engine that can process the movement of trucks and containers in real-time. It’s now time to unlock the potential of that engine by building SaaS applications that leverage the vision engine to transform the logistics industry.

We are seeking a Computer Vision Researcher with ideally 3 years of relevant experience to join our team. The appointee will work within the Research team and focus on cutting-edge research projects for high-quality publications and IP generations.

Responsibilities: 

  • Contribute to the research, development and implementation of innovative methods and in applied artificial intelligence.

  • Addressing real-world challenges derived from the company’s mission  via computer vision and deep learning technologies, particularly in the topic of text and object recognition.

  • Prepare, submit and publish high-quality journals and internationally-leading conferences 

  • Support the capture of intellectual property and prepare technical material for the submission of patent and grant applications.

  • Educate and support (e.g. via theoretical  problem solving or research-grade implementation) the Vision Engine team in their mission to deploy computer vision methods in the company product.

 

Required skills and qualifications: 

  • A PhD degree in Computer Vision, Machine Learning, or a closely related field (or be on the course of getting one very soon at the time of application).

  • A track record of publication in high-quality academic conference papers and/or journals commensurate with career stage.

  • Detailed and highly specialised knowledge and understanding of developments at the forefront of Computer Vision, Deep Learning, Machine Learning.

  • Extensive knowledge of Machine Learning/Deep Learning frameworks and libraries.

  • Proficiency in Python.

  • Strong communication and teamwork skills.

Preferred skills and qualifications: 

  • Experience in large-scale outdoor scene text spotting and visual object categorisation. 

  • Experience in vision-language models and multi-task learning.

  • Successful remote working experience in a technical team.

Further Information: 

  • The research work in this role is supported by a team lead, principal researcher, computational resources, and a dedicated (company-wide) data gathering and curation team with whom the appointee will work closely.

  • The appointee will not be required to work directly on company deployments or be solely responsible for code within shipped products.

 

What We Offer: 

Joining the Terminal team means being part of a dynamic, innovative environment where your work directly impacts the future of logistics and the global supply chain. You will work closely with a team of experts passionate about operational excellence and technological innovation.

We offer;

  • Competitive Pay

  • Private Health Insurance

  • Private Dental Insurance

  • Group Life Insurance, Critical illness Insurance, and Income Protection Insurance

  • Pension scheme

  • Meal allowance and more..

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The Company
45 Employees
Remote Workplace
Year Founded: 2023

What We Do

We build AI that makes logistics yards smart

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