Faculty is an applied AI company that helps organisations who have the scale, data, and foresight to adopt AI into their business. We're helping make AI real across society by providing a unique combination of strategy, software and skills to our customers: everything needed to successfully create value from AI. Founder-led and with over 80 PhDs, we're a team of specialists with experience across healthcare, finance, government, retail, engineering, construction and a host of other sectors.
We believe that AI should be trustworthy, impactful and beneficial across society. Those principles have shaped our work with more than 230 organisations across the public and private sectors as we help them use AI to act faster, make better decisions and understand more deeply. Thanks to our dedicated AI safety research programme, we're constantly refining our systems to make AI safer, more secure and more reliable.
*About the role:*
Customer engineering's mission is to help customers get the most out of Faculty's technology. It is a cross-cutting function that touches on every part of our business.We have an amazing set of clients and projects ranging from counter terrorism, government agencies, retail, marketing, healthcare to financial services. You will build strong relationships with our customers through technical leadership, demonstrating the value of our products and helping to solve engineering challenges.
Our Customer Engineering Team is responsible for to helping customers get the most out of Faculty's technology. As a machine learning engineer you will work on real outcomes that get deployed into production. We're a rapidly growing organisation, so roles are dynamic and subject to change. Your role will evolve alongside business needs, but you can expect your key responsibilities to include:
* Design and build world class machine learning outcomes using the latest open source technologies.
* Work with our team of data scientists to build deployable machine learning software.
* Gain exposure to a wide variety of data science and data engineering projects spanning almost every industry.
* Learn and apply the latest techniques in data science and machine learning.
* Have the opportunity to publish blog articles about the Faculty's views on machine learning in production and our recommendations for related techniques.
Bespoke Software Delivery:
* Engage with technical people in our clients from the outset to understand their technical requirements and co-design the best approach to engineering for them.
* Partner with commercial staff and data scientists to scope client work, at proposal and initiation stages.
* Ensure the bespoke software we write is well engineered and of production quality.
* Development and enhancement of machine learning software with data scientists
* Solve technical issues for customers to show how our platform can make them more productive, collaborative and innovative.
* You will liaise with the product team to stay on top of industry trends, devise enhancements to our platform and help articulate opportunities and threats to the platform space.
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. 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 your 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.
* Commercial experience in a customer facing software engineering role
* Commercial experience of machine learning including understanding of the main machine learning areas and widely used techniques and algorithms.
* 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
* Relevant degree or industry experience demonstrating strong software and systems engineering fundamentals.
* 3+ years of experience in software engineering which should include programming in Python.
* R, Matlab, Scala, Java or C++ as an additional language is a plus
* Working proficiency with Unix-based operating systems and general systems administration knowledge (i.e. command line interface, SSH, handling permissions, file limits, networking, resource utilisation, etc.).
* Comfortable in a high-growth startup environment.
* Outstanding verbal and written communication.
* Excitement about working in an dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to execution
* Eligibility for UK Security Clearance is a bonus.
* A learning environment: Faculty is dedicated to growing and learning. This translates into dedicated learning time every Friday morning, pair programming with a more experienced engineer, frequent lunch and learns, and plenty of tech talks.
* Genuinely flexible working: We believe people have needs, responsibilities and interests that require something different to a strict 9-6 working day. We trust people to organise and take accountability for their own work and do our best to support their lives outside Faculty.
* Unlimited holidays
* Cycle to work
* £100 Work from Home equipment fund for any work-essential tech or home office equipment (on top of your laptop, of course)
* Access to TechScheme monthly personal tech repayment process
* Sanctus mental health
* Telephone call
* Coding Test
* Technical Interview
* Final Interview
Machine Learning, Docker, Kubernetes, PythonMachine Learning, Docker, Kubernetes, Python, R, Matlab, Scala, Java, C++