Senior Computer Vision Engineer, Neurolabs

£55-85k

0.5 - 1.0% Equity option

Python
Tensorflow
PyTorch
Keras
Mid and Senior level
Remote in EU, UK
London

More information about location

Neurolabs

Business processes automation software

Otta Certified

Job no longer available

Neurolabs

Business processes automation software

1-20 employees

B2BArtificial IntelligenceComputer VisionMachine LearningAutomation

Otta Certified

Job no longer available

£55-85k

0.5 - 1.0% Equity option

Python
Tensorflow
PyTorch
Keras
Mid and Senior level
Remote in EU, UK
London

More information about location

1-20 employees

B2BArtificial IntelligenceComputer VisionMachine LearningAutomation

Company mission

Neurolabs' mission is to democratise computer vision.

Role

Who you are

  • MSc or PhD in Computer Science/Physics/Maths or related quantitative subject
  • 3+ years experience shipping computer vision solutions or working in a research-driven environment where the core focus is computer vision
  • Strong grasp of latest cutting edge research in object detection, similarity, transfer & few-shot learning
  • Keen interest in Computer Graphics is a plus
  • Good written and excellent spoken communication skills as well as attention to detail
  • Proficient with Python and machine learning frameworks such as PyTorch, Tensorflow, Keras, PyTorch Lightning

What the job involves

  • Lead and manage the efforts to scale our computer vision pipeline to support dozens of clients
  • Design, implement and deploy deep learning techniques & architectures for visual search and few-shot learning using synthetically generated data
  • Collaborate with team members and lead the research efforts towards advancing Neurolabs' computer vision capabilities

Application process

  • Apply via Otta or our Job site
  • 30 minute intro call with our hiring manager - to get to know you as a person, understand your background and experience, and see if you could be a good culture fit for our team. It’s also an opportunity for you to get to know us better - what Neurolabs does, what our vision is and whether you think we are a good cultural fit for you.
  • Technical interview - to better understand your technical capabilities. You’ll have an interview with one of our senior team members or a teammate and the focus will be on understanding your high-level technical skills. (ca. 30 - 45 minutes)
  • Skills assessment - for us to evaluate your skillset and technical abilities. This interview stage is split into 2 parts: 1. Take-home programming assignment - your chance to show the team where your technical strengths lie 2. Programming rundown - for your potential team & manager to assess your coding abilities and to analyse and interpret your thinking and process during the programming assignment (1.5 - 2 hours)
  • Founder’s interview - a chance for all three founders Paul, Patric & Remus to meet you, and for you to meet them. This is another opportunity for both sides to determine whether you and Neurolabs see each other as technical and cultural fits and whether there is alignment between the founders’ vision and your motivation and drive. (ca. 45min )

Salary benchmarks

Otta's take

Sam Franklin headshot

Sam Franklin

CEO of Otta

Neurolabs is a Computer Vision (CV) platform allowing users to build custom image recognition algorithms using 3D models. It substitutes the expensive and rare real-world data required to train CV algorithms with synthetically generated data to provide massive, rich and diverse low-cost data sets at a fraction of the cost and time.

Synthetic Data combines advanced machine learning techniques and CGI models to create large sets of perfectly labelled data that is optimised for CV. The company’s proprietary CV technology enables rapid state-of-the-art development of object recognition solutions across multiple use cases and industries, accelerating the automation of repetitive visual tasks.

Its technology empowers both small and large customers to implement CV applications with minimal resources and costs — no coding required, no tedious data labelling, and no image gathering. Its partners use the technology to automate generic object recognition tasks in industries ranging from hospitality to retail and manufacturing.

Although ‘automation’ is a term that is often associated with job losses, Neurolabs’ vision is to enhance the capabilities of workers, not replace them outright, and with its recent seed funding it will soon be well on its way to achieving this.

Insights

Most candidates hear
back within 2 weeks

Company

Employee endorsements

Challenging work

"The projects which are developed in Neurolabs are focused heavily on current research methods, therefore the development is fast-paced and..."

Funding (last 2 of 4 rounds)

May 2022

$3.6m

SEED

Jul 2020

$1.1m

SEED

Total funding: $4.9m

Company benefits

  • Equity options
  • Flexible working hours from home or our offices in Edinburgh or London
  • 34 days annual leave (incl. public holidays in your residence country)
  • Bi-annual company retreat and bi-annual team meetings (workation)
  • Private medical insurance, including mental health, dental, opticians cover, and business as well as personal travel insurance. 🇬🇧
  • Cycle to Work Scheme 🇬🇧

Company values

  • We're purposeful → We're driven towards something that motivates us intrinsically
  • We're authentic → We are strongly against 'rule'-based, pretend behaviour. We will always work to make Neurolabs a place where all of us can be our real selves
  • We're reliable → Getting things done and taking responsibility for your work is critical
  • We're respectful → We all come from diverse backgrounds and therefore must work to understand, appreciate and celebrate our differences
  • We're a community → We are supportive, kind and generous to each other

Company HQ

Holborn, London, UK

Founders

Previously Computer Vision Lead at Hudl and software engineer at Schlumberger.

Former market risk analyst at Bank of America & has a Master of Science in AI.

Previous Technology Analyst at J.P. Morgan before obtaining a PhD in Machine Learning from the University of Edinburgh.

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