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Senior research scientist

London
Yoti
Research scientist
Posted: 2 February
Offer description

Who We Are

Born in 2014, Yoti is a digital identity and biometric technology company that makes it safer for people to prove who they are. The Yoti app was designed with privacy at its core, giving people a secure way to prove their identity and share third-party credentials with organisations and other people.

Today, we have over seventeen million app downloads around the world. Weve expanded our offering to a suite of business solutions that span identity verification, age verification and estimation, e-signing, AI anti-spoofing technologies and we continue to think of innovative new offerings.

From day one, weve been working to fix an outdated identity system. This is not a journey we make on our own but with policy advisors, think tanks, researchers, academics, humanitarian bodies, our users and everyday people. We are committed to solving identity problems through grassroots research and social purpose initiatives.

Purpose of the Role : To work on projects in the fields of Computer Vision, Machine Learning and Deep Learning

Role Dimensions : Reports to Head of R&D / CTO; within R&D team.

Principal Responsibilities

Research on large scale classification such as face recognition, verification and face anti-spoofing using deep learning. Investigate new deep learning network architectures, cost functions and optimisation techniques for efficient feature extraction.
Data preparation, augmentation and preprocessing for training deep learning models. Investigate speed-up optimisations to train DNNs faster.
Maintain an expert level knowledge of the related academic literature on large scale classification with deep learning and being up-to-date with recent advances.
To implement academic papers into functional prototypes.
Mentoring of junior R&D team members on technical aspects, reviewing merge requests and assisting in the debugging of issues that can occur during model development.
Presenting the evaluated performance of models to people outside the R&D team, i.e. to people in other teams.

Knowledge, Skills, Qualifications And Experience

PhD in the areas of computer vision, machine learning, image processing, or the ability to demonstrate equivalent expertise.
Strong knowledge of DNN theory and practical experience of applying DNN in computer vision
Strong knowledge of at least one deep learning frameworks (Tensorflow/PyTorch/Jax)
Proficiency with Python coding
Proficiency working with Git inside a team, including appropriate use of branches and merge requests
Ability to write clean and well maintained code
Attention to detail
Strong analytical and problem-solving skills with the capability of implementing academic papers into functional prototypes.
A solid working knowledge of the Linux command line
Working with Docker, and the ability to create new docker images for specific use cases
The ability to work independently on the technical aspects of a self-contained project, e.g. being able to develop a model from the specification for that model through to doing a thorough analysis of the trained model

Interview Process

Stage 1: Call with a talent acquisition team member (30 minutes)

Stage 2 : Call with the hiring manager (45 minutes)

Stage 3 : Coding Interview

Stage 4 : Research Presentation with the R&D Team (2 hours)

Stage 5 : Call with Head of R&D ( 30 minutes)

Whats in it for you?

Flexible working
Performance based discretionary annual bonus
Share Options
Internal Share Market
Private Medical Insurance
Life Insurance
Pension
Cycle to work scheme
Electric Car Scheme
25 days holiday (plus bank holidays)
5 fully paid days of Selfie Time - for your own personal development, volunteering, charity events, etc
Team and company activities, Social clubs.
Continuous learning opportunities (Annual Training budgets, conferences etc)

This is a great opportunity to join a company that is leading the way for innovative and responsible identity verification. Were looking for people who can adapt to a fast-paced environment, as well as champion our brand and what we stand for. We value a positive attitude and people who have a collaborative, creative and transparent approach to solving problems.

AI Usage during the recruitment process

Please read our AI Usage in Recruitment policy to know more about how Yoti uses AI in the recruitment process and our stance on how candidates can use AI during the interview process.

We believe in equal opportunities

It takes a diverse community of passionate, talented and committed people to build a simpler, more secure way of proving identity. Were an equal opportunity employer, so we welcome applications from people of all backgrounds, with different outlooks and experiences.

We are proud to be a Disability Confident employer and were committed to making our recruitment process as inclusive and accessible as possible.

If you have a disability or long-term condition and need any adjustments or support during the application or interview process, please let us know well do everything we can to support you and to enable you to bring your best self to our hiring process.

Pre-employment checks

If your application is successful please be aware that as part of our pre-employment checks:

We will check your details against fraud prevention databases. We will check identity; address match; PEPs and sanctions; bank validation, verification, fraud checks, negative data (CCJ, bankruptcy). If our investigations identify fraud or other criminal offences both when applying for a job and during your employment, we will record the details on the relevant fraud prevention databases. This information may be accessed from the UK and other countries and used by law enforcement agencies and other organisations to prevent fraud.

Please contact to get information on which fraud prevention databases we use.

Talent Pool

If we consider that you might be suitable for other roles in the future, we will keep your details so we can contact you about these other roles. If you do not want us to keep your details for this purpose, please e-mail or let us know at any stage of the recruitment process. For more information please read our Applicant Privacy Notice.

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