Deep Learning Engineer, V7 Labs

Applied Research/Vision

Salary not provided

Elixir

Erlang

PyTorch

Junior and Mid level

London

Remote from Europe, UK

Speed up ML development, automate tasks with AI, and improve efficiency.

Job no longer available

Speed up ML development, automate tasks with AI, and improve efficiency.

21-100 employees

B2BArtificial IntelligenceBig dataComputer VisionSaaS

Job no longer available

Salary not provided

Elixir

Erlang

PyTorch

Junior and Mid level

London

Remote from Europe, UK

21-100 employees

B2BArtificial IntelligenceBig dataComputer VisionSaaS

Company mission

We exist to help turn valuable human knowledge into cutting edge AI, and play a major role in the evolution of AI as a technology.

Job

Company

Role

Who you are

Experience in deep learning, from understanding the underlying math, to the ability to illustrate landmark papers within the vision domain (given enough prep time)
Evidence of individual contribution to challenging DL/ML projects
A CV that demonstrates an early interest in computer science
A curious, scientific mind
Fluent in English

What the job involves

General purpose models
Instance and semantic segmentation (centroid approaches, high-fidelity semantic segmentation for labelling)
Multi-task models (eg. Taskonomy and related papers)
Auto-ML in vision
Ultra-large model backbones (eg. MOCO and related papers)
We're based on PyTorch, our BE is in Elixir (erlang), and FE is Vue.js. We make GPU machines available both at our office or in the cloud. We are regular CVPR/NeurIPS/ECCV attendees and in normal times attend as a team
An inference and training orchestration engine to run any model request in real-time across a library of computer vision models
Several implementations of instance-segmentation architectures like Mask-Rcnn, CenterMask, and object detection architectures like VoVnet
Configuration parameters to enable the training of models across various dataset sizes, image sizes, and relative annotation sizes and amounts
The development of deep image retrieval systems to automatically rank datasets by content-based parameters without the need of prior training

Salary benchmarks

Our take

AI is currently utilised across multiple industries, requiring companies to continuously collect, organise and label image data so that AI models will be able to adapt to new scenarios. V7 Labs is a computer vision platform that helps AI teams develop vision-based models that are learning continuously from training data with minimal human supervision.

V7 distinguishes itself in the market by condensing the most effective tools for organizing datasets into a single SaaS platform. The company says that using only 100 human-annotated examples in its toolkit can label the rest of the training data autonomously. Although its main business specialisations are in medicine and health sciences, its product is being picked up by tech companies in other sectors, and it now counts more than 300 customers including Siemens and GE Healthcare.

The startup has recently raised funding in a Series A round led by Radical Ventures and Temasek. It will use this investment to hire more engineering and sales talent, develop its product, and expand its market share.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

31% female employees

74% employee growth in 12 months

Glassdoor (3.8)

Company

Funding (last 2 of 3 rounds)

Nov 2022

$33m

SERIES A

Jul 2021

$7m

SEED

Total funding: $50m

Company benefits

Top 15% quartile equity options plan through an EMI scheme
Private Healthcare via Vitality
Learning and Development wallet of £800 per year
Monthly well being and mental health budget
Personalised benefits platform via Thanks Ben
Enhanced parental leave
25 days paid holiday with unlimited additional days
4-day company-wide and 4 day departmental retreats in stunning locations
Visit London to meet us in our HQ. We have a barista & plenty of snacks
Hybrid working with flexibility or remote working
Temporary work from anywhere for one month in the calendar year
Paid tickets, accommodation, and travel to relevant conferences, nationally or internationally (NeurIPS, ICCV, CVPR, ...) to expand your network & knowledge during normal times
Apple hardware provided plus a £500 budget from home office equipment

Company HQ

Fitzrovia, London, UK

Leadership

Alberto Rizzoli

(Co-Founder & CEO)

Previously CEO at Aipoly, the first smartphone engine for convolutional neural network. Management & Stats grad at Cass Business School & Singularity University. Never had a real job.

Simon Edwardsson

(Co-Founder)

Studied Computer Engineering at Chalmers University of Technology. Previously Co-Founder at Aipoly and Lead R&D Engineer at Retail Solutions Inc.

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