Machine Learning Engineer, Faculty
Salary not provided
AWS
Docker
Kubernetes
Python
Tensorflow
Azure
Scikit-Learn
PyTorch
Junior, Mid and Senior level
London
More information about location
2+ days a week in office
Enabling clients to use cutting edge AI to improve the performance of their business
Posted today
Enabling clients to use cutting edge AI to improve the performance of their business
201-500 employees
B2BArtificial IntelligenceBig dataMachine Learning
Posted today
Salary not provided
AWS
Docker
Kubernetes
Python
Tensorflow
Azure
Scikit-Learn
PyTorch
Junior, Mid and Senior level
London
More information about location
2+ days a week in office
201-500 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
- You can view our company principles here. We look for individuals who share these principles and our excitement to help our customers reap the rewards of AI responsibly
- To succeed in this role, you’ll need the following - these are illustrative requirements and we don’t expect all applicants to have experience in everything (70% is a rough guide):
- 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
- 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
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 Government & Public Services arena
- Because of the potential to work with our clients in the National Security space, you will need to be eligible for Security Clearance, details of which are outlined when you click through to apply
- 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
- 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
- As a rapidly growing organisation, roles are dynamic and subject to change
- 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 determine how they can utilise AI, and then assist them in implementing the necessary skills, strategy, and software.
The team has developed a platform with a large cloud computing space for accessing vast amounts of data for use in designing and testing AI models. Frontier, its Design Intelligence platform, develops digital twins for its customers, which give them more insight into useful applications for AI. Applied AI is Faculty's consulting division, working with clients to build and deploy tailored AI solutions.
Faculty has worked with clients in a range of different industries across the public and private sectors, including healthcare, retail, government and energy.
Steph
Company Specialist at Welcome to the Jungle
Insights
Top investors
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
$39.8m
SERIES A
Nov 2019
$10.5m
SERIES A
Total funding: $52.3m
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
- Grow the Best Team - Only hire people you’re convinced will make Faculty better. Take others’ development as seriously as your own. Build strong and collaborative teams
- Do Great Work - Master your craft. Take pride in your work, even when no one is watching. Demand the highest standards from yourself and others. Work hard, but do it sustainably
- Be Humble & Kind - Recognise that you’re always learning, and have something to learn from everyone. Always make the decision that is best for faculty, but treat people kindly as you do it
- Act with Integrity - Have the courage to maintain integrity even when it’s costly to do so. Demand this from others without hesitation
- Seek Truth - Seek the truth over winning the argument. Understand the root cause. Create an atmosphere in which the best idea succeeds, regardless of who or where it comes from.
- Maximise Impact - Care about the impact of your work. Find the thing that is most important to your customer. Design the best solution, not just what’s easiest or fashionable. Get it done fast. Make sure nothing falls through the cracks.
Company HQ
Old Street, London, UK
Articles
Leadership
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.
Diversity, Equity & 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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