Machine Learning Engineer, Faculty
Life Sciences
Making AI real
Job no longer available
Making AI real
501-1000 employees
Job no longer available
501-1000 employees
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
- 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
- At Faculty, your attitude and behaviour are just as important as your technical skill. We look for individuals who can support our values, foster our culture, and deliver for our organisation
- 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
- 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 interest in the full machine learning lifecycle, including deploying trained machine learning models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch
- Understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniques
- Experience in Software Engineering including programming in Python
- Technical experience of cloud architecture, security, deployment, and open-source tools. Hands-on experience required of at least one major cloud platform
- Demonstrable experience with containers and specifically Docker and Kubernetes
- Comfortable in a high-growth startup environment
- 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
- 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 in the Life Science
- 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. To enable this, we work in cross-functional teams with representation from commercial, data science, product management and design specialities to cover all aspects of AI product delivery
- The Machine Learning Engineering team is responsible for the engineering aspects of our customer delivery projects
- 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
- 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
Otta's take
Xav Kearney
CTO of Otta
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.
Insights
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 2021
$38.7m
SERIES A
Nov 2019
$10.5m
SERIES A
Total funding: $51.2m
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
Articles
Founders
Marc Warner
(CEO)Previously a Marie Curie Fellow in Physics at Harvard University, specialising in quantum sensing
Andrew Brookes
(CTO)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 & Inclusion at Faculty
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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