Senior Research Scientist

Yoti; United Kingdom; On-site; GBP 50,000 - GBP 70,000; Full time

Job summary

A leading technology firm in the UK is seeking a skilled Computer Vision Scientist to work on deep learning projects. You will research large scale classification and implement prototypes from academic papers while mentoring junior team members. Candidates should have a PhD in a relevant field, strong knowledge of deep learning frameworks, and be proficient in Python. The position offers flexible working, bonuses, and a supportive team environment.

Benefits

Flexible working

Performance-based annual bonus

Share options

Private medical insurance

Life insurance

Pension scheme

25 days holiday plus bank holidays

Continuous learning opportunities

Qualifications

• PhD or equivalent expertise in computer vision or machine learning.
• Strong theoretical and practical knowledge of DNN.
• Experience in implementing academic research into prototypes.

Responsibilities

• Conduct research on face recognition and anti-spoofing using deep learning.
• Prepare and preprocess data for training models.
• Mentor junior team members and assist with technical reviews.

Skills

Deep learning frameworks (Tensorflow/PyTorch/Jax)

Python coding

Problem-solving skills

Linux command line

Docker

Education

PhD in computer vision, machine learning, or equivalent

Tools

Git

Job 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. We’ve 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From day one, we’ve been working to fix an outdated identity system.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)

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 [e-mail] 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 [e-mail] or let us know at any stage of the recruitment process. For more information please read our Applicant Privacy Notice.