Senior Machine Learning Engineer, Faculty

Salary not provided
AWS
Docker
Kubernetes
Python
Tensorflow
Azure
Scikit-Learn
PyTorch
Senior and Expert level
London

1+ day a week in office

Faculty

Making AI real

Open for applications

Faculty

Making AI real

501-1000 employees

B2BArtificial IntelligenceBig dataMachine Learning

Open for applications

Salary not provided
AWS
Docker
Kubernetes
Python
Tensorflow
Azure
Scikit-Learn
PyTorch
Senior and Expert level
London

1+ day a week in office

501-1000 employees

B2BArtificial IntelligenceBig dataMachine Learning

Company mission

To help organisations across the public and private sectors use AI to understand more deeply, make better decisions and act faster.

Role

Who you are

  • Because of the potential to work with our UK Defence clients, you will need to be eligible for SC clearance and willing to work up to three days per week on site with these customers, which may require travel to locations outside of our London base
  • You are engineering-focused, with a keen interest and working knowledge of operationalised machine learning
  • You have a desire to take cutting-edge ML applications into the real world
  • We like people who combine expertise and ambition with optimism -- who are interested in changing the world for the better -- and have the drive and intelligence to make it happen. If you’re the right candidate for us, you probably:
  • Think scientifically, even if you’re not a scientist - you test assumptions, seek evidence and are always looking for opportunities to improve the way we do things
  • Love finding new ways to solve old problems - when it comes to your work and professional development, you don’t believe in ‘good enough’. You always seek new ways to solve old challenges
  • Are pragmatic and outcome-focused - you know how to balance the big picture with the little details and know a great idea is useless if it can’t be executed in the real world
  • Understanding of, and experience with the full machine learning lifecycle
  • Working with Data Scientists to deploy trained machine learning models into production environments
  • Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch
  • Experience with software engineering best practices and developing applications in Python
  • Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud providers (AWS, GPS or Azure)
  • Demonstrable experience with containers and specifically Docker and Kubernetes
  • An understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniques
  • Demonstrable experience of managing/mentoring more junior members of the team
  • Outstanding verbal and written communication
  • Excitement about working in a dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to execution

What the job involves

  • This role is situated within our Applied AI consultancy, which serves clients across UK Defence, Government, Life Sciences, Energy, Banking and Retail
  • As a Machine Learning Engineer, you will work in the business area where the need is greatest and this may change from time-to-time, depending on our external client requirements
  • We are a rapidly growing business and require all our employees to be versatile across sectors and confident to be client-facing within those
  • You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning
  • The work you do will help our customers solve a broad range of high-impact problems across multiple sectors - examples of which can be found here
  • You will develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements
  • You will support both technical, and non-technical stakeholders, to deploy ML to solve real-world problems
  • Our Machine Learning Engineerings are responsible for the engineering aspects of our customer delivery projects
  • As a Machine Learning Engineer, you’ll be essential to helping us achieve that goal by:
  • Building software and infrastructure that leverages Machine Learning
  • Creating reusable, scalable tools to enable better delivery of ML systems
  • Working with our customers to help understand their needs
  • Working with data scientists and engineers to develop best practices and new technologies; and
  • Implementing and developing Faculty’s view on what it means to operationalise ML software
  • Your role will evolve alongside business needs, but you can expect your key responsibilities to include:
  • Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems
  • Working with senior engineers to scope projects and design systems
  • Providing technical expertise to our customers
  • Technical Delivery

Salary benchmarks

Our take

Faculty work with companies such as Samsung, the BBC, and Just Eat to figure out what they could do with AI, and then help them to do it through implementing the right skills, strategy and software.

The team have developed a platform with large cloud computing space for accessing large amounts of data usable to design and test AI models. As businesses realise the importance of using data to drive growth and stay competitive, Faculty have focused on making AI real through real world deployments and aim provide data to organisations so that they can make better decisions.

Faculty has worked with clients in a range of different industries, including healthcare, retail, government and energy. They are just one of the many companies utilising AI, but it’s their ability to work alongside organisations and apply the findings that will really help them to succeed.

Steph headshot

Steph

Company Specialist at Welcome to the Jungle

Insights

Top investors

Some candidates hear
back within 2 weeks

35% female employees

19% employee growth in 12 months

Company

Employee endorsements

Autonomy

"People here get a lot of trust to figure things out. They also get the chance to earn a lot of responsibility at a relatively early stage in their..."

Funding (last 2 of 3 rounds)

May 2020

$39.4m

SERIES A

Nov 2019

$10.5m

SERIES A

Total funding: $51.9m

Company benefits

  • Hybrid working: We believe people have needs, responsibilities and interests that require something different to a strict working day. We trust people to organise and take accountability for their own work and do our best to support their lives outside Faculty. We provide you with all you need to work from home, including a laptop, keyboard, chair…even Sony headphones!
  • Equity, we want you to benefit from Faculty’s growth and success
  • Unlimited holidays: We encourage each other to use this time to take a break, work on personal projects, or to spend time with their friends and family
  • Fantastic private health, optical and dental cover, for you & your family - including 24/7 unlimited virtual private GP appointments and covering pre-existing medical conditions
  • Access to mental health coaching with Sanctus
  • Lunch weekly, and more fruit, drinks and snacks than you could ever eat (for office-based employees)
  • We work hard and make sure we enjoy what we do. So we have frequent socials and informal get-togethers to help make sure you enjoy your time with us. You’ll make friends and professional connections that will last a lifetime

Company values

  • Seeking truth - We ask ourselves and each other the difficult questions, and make sure the best idea always wins
  • Execute pragmatically - We focus on what’s important, make decisions fast, and adapt as needed
  • Foster talent - At its core, Faculty is about fostering talent. It’s deeply ingrained in our DNA and we give our people the support and time they need to be the best they can be
  • Invert, always invert - We treat nothing as set in stone, and constant seek new ways to do things better

Company HQ

Old Street, London, UK

Leadership

Previously a Marie Curie Fellow in Physics at Harvard University, specialising in quantum sensing

Previously a CTO at Hillgate and Vice President at BlackRock

Angie Ma

(Co-Founder)

Previously a Scientific Consultant at Bio Nano Consulting


People progressing

Oana joined Faculty 3 years ago, swapping investment banking for tech. She initially joined as a Senior Product Designer, progressing to Product Manager and most recently to Director of Product.

After completing her Phd in Mathematics and working in research, Kim was introduced to Faculty through our Fellowship Programme. Starting as a Data Scientist, and recently being promoted.

Diversity, Equity & Inclusion at Faculty

Angie Ma headshot

Angie Ma (Co-Founder)

  • AI changes everything, and so must we to make sure our people reflect the real diversity of society. We believe that recruiting talent with diverse experiences, perspectives and backgrounds encourages people to think differently and be more creative
  • We welcome difference whether it’s ethnicity, religion, age, gender, gender identity, sexual orientation or disability so please be yourself!

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