Machine Learning Engineer

About Faculty At Faculty, we transform organisationalperformance through safe, impactful and human-centric AI. With adecade of experience, we provide over 300 global customers withsoftware, bespoke AI consultancy, and Fellows from our awardwinning Fellowship programme. Our expert team brings togetherleaders from across government, academia and global tech giants tosolve the biggest challenges in applied AI. Should you join us,you’ll have the chance to work with, and learn from, some of thebrilliant minds who are bringing Frontier AI to the frontlines ofthe world. We operate a hybrid way of working You'll split yourtime across client location, Faculty's Old Street office andworking from home depending on the needs of the project. For thisrole, you can expect to be client-side for up to three days perweek at times and working either from home or our Old Street officefor the rest of your time. About the Role You will design, build,and deploy production-grade software, infrastructure, and MLOpssystems that leverage machine learning. The work you do will helpour customers solve a broad range of high-impact problems in ourDefence team - examples of which can be found here. Because of thepotential to work with our clients in the National Security space,you will need to be eligible for Security Clearance, details ofwhich are outlined when you click through to apply. What You'll BeDoing You are engineering-focused, with a keen interest and workingknowledge of operationalised machine learning. You have a desire totake cutting-edge ML applications into the real world. You willdevelop new methodologies and champion best practices for managingAI systems deployed at scale, with regard to technical, ethical andpractical requirements. You will support both technical, andnon-technical stakeholders, to deploy ML to solve real-worldproblems. Our Machine Learning Engineers are responsible for theengineering aspects of our customer delivery projects. As a MachineLearning Engineer, you’ll be essential to helping us achieve thatgoal by: - Building software and infrastructure that leveragesMachine Learning; - Creating reusable, scalable tools to enablebetter delivery of ML systems; - Working with our customers to helpunderstand their needs; - Working with data scientists andengineers to develop best practices and new technologies; -Implementing and developing Faculty’s view on what it means tooperationalise ML software. As a rapidly growing organisation,roles are dynamic and subject to change. Your role will evolvealongside business needs, but you can expect your keyresponsibilities to include: - Working in cross-functional teams ofengineers, data scientists, designers and managers to delivertechnically sophisticated, high-impact systems; - Working withsenior engineers to scope projects and design systems; - Providingtechnical expertise to our customers; - Technical Delivery. WhoWe're Looking For You can view our company principles here. We lookfor individuals who share these principles and our excitement tohelp our customers reap the rewards of AI responsibly. We likepeople who combine expertise and ambition with optimism -- who areinterested in changing the world for the better -- and have thedrive and intelligence to make it happen. If you’re the rightcandidate for us, you probably: - Think scientifically, even ifyou’re not a scientist - you test assumptions, seek evidence andare always looking for opportunities to improve the way we dothings; - Love finding new ways to solve old problems - when itcomes to your work and professional development, you don’t believein ‘good enough’. You always seek new ways to solve old challenges;- Are pragmatic and outcome-focused - you know how to balance thebig picture with the little details and know a great idea isuseless if it can’t be executed in the real world. To succeed inthis role, you’ll need the following - these are illustrativerequirements and we don’t expect all applicants to have experiencein everything (70% is a rough guide): - Understanding of, andexperience with the full machine learning lifecycle; - Working withData Scientists to deploy trained machine learning models intoproduction environments; - Working with a range of models developedusing common frameworks such as Scikit-learn, TensorFlow, orPyTorch; - Experience with software engineering best practices anddeveloping applications in Python; - Technical experience of cloudarchitecture, security, deployment, and open-source tools ideallywith one of the 3 major cloud providers (AWS, GCP or Azure); -Demonstrable experience with containers and specifically Docker andKubernetes; - An understanding of the core concepts of probabilityand statistics and familiarity with common supervised andunsupervised learning techniques; - Demonstrable experience ofmanaging/mentoring more junior members of the team; - Outstandingverbal and written communication; - Excitement about working in adynamic role with the autonomy and freedom you need to takeownership of problems and see them through to execution. What wecan offer you: The Faculty team is diverse and distinctive, and weall come from different personal, professional and organisationalbackgrounds. We all have one thing in common: we are driven by adeep intellectual curiosity that powers us forward each day.Faculty is the professional challenge of a lifetime. You’ll besurrounded by an impressive group of brilliant minds working toachieve our collective goals. Our consultants, product developers,business development specialists, operations professionals and moreall bring something unique to Faculty, and you’ll learn somethingnew from everyone you meet. #J-18808-Ljbffr