Senior Research Scientist in London

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. We have 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 From day one, we have been working to fix an outdated identity system.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.
• Implement academic papers into functional prototypes.
• Mentor junior R&D team members on technical aspects, review merge requests and assist in debugging issues that can occur during model development.
• Present 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 framework (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)

What’s 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. We’re 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. We’re 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 we’re 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 — we’ll 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.