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Machine Learning Engineer

Salary:
38,396 P.A. ?
Location: London
Company: Faculty of Advocates
Hours: Full time
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Faculty is looking for Machine Learning Engineers to join our growing team. You will design, build, and deploy production grade software, infrastructure, and MLOps systems that leverage machine learning to help our customers solve high impact problems.

We have a wide-ranging set of customers and projects including: counter terrorism, government departments, retail, marketing, healthcare, built environment, energy, and financial services.

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 opinionated best practices for managing AI systems deployed at scale, with regards 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.

Who we are

Faculty is one of Europe’s leading applied artificial intelligence companies. We build, deploy and operate AI solutions to increase our customers’ performance and help them realise their full potential. 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 understand more deeply, make better decisions and act faster.

Your responsibilities

The Machine Learning Engineering team is 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.

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:

  • 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

Who you are

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.

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 all these (70% is a rough guide) :

  • 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 which ideally would 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.).
  • 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 an dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to execution

Benefits

You’ll join a diverse and distinctive team. We come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. This curiosity pushes us to seek truth and understanding in everything we do, to execute work in a nimble and pragmatic manner, to foster talent in one another and always to challenge assumptions.

Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to advance our goal of making artificial intelligence real. All our people bring something unique to Faculty, and you’ll learn something new from everyone you meet. You’ll also have the opportunity to make your mark on a high-growth start-up now poised to expand internationally.

Fostering talent is one of our core values, it’s built into our culture and what we offer.

  • An incredible, unique learning and development system: Faculty was founded by people who are passionate about continuous learning, and adding value to our people.
  • Genuinely flexible 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.
  • 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.
  • Parental Leave: We offer a progressive, equal, and generous parental leave policy. All parents are given 15 weeks leave at full pay in addition to statutory time off.
  • Fantastic private health, optical and dental cover, including 24/7 unlimited virtual private GP appointments.
  • Breakfast and more fruit, drinks and snacks than you could ever eat (for office-based employees).
  • Did we mention Yoga?
  • You’ll make friends and professional connections that will last a lifetime. 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.
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