Machine Learning Engineer

Навыки

• AWS
• Azure
• Docker
• Google Cloud
• Kubernetes
• Machine Learning
• Python

О компании и продукте

• Our Defence team is focused on building and embedding human-centered AI solutions which give our nation a competitive edge in the defence sector. We collaborate with our clients to bring ethical, reliable and cutting-edge AI to high-stakes situations and maintain the balance of global powers essential to our liberty.
• Because of the nature of the work we do with our Defence clients, you will need to be eligible for UK Security Clearance (SC) and willing to work between 2 to 4 days per week on-site with these customers which may require travel to locations throughout the UK.
• When not required on client sites, you’ll have the flexibility to work from our London office or remotely from elsewhere within the UK.
• Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse clients.

Задачи

• Building and deploying production-grade ML software, tools, and infrastructure
• Creating reusable, scalable solutions that accelerate the delivery of ML systems
• Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges
• Leading technical scoping and architectural decisions to ensure project feasibility and impact
• Defining and implementing Faculty’s standards for deploying machine learning at scale
• Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders
• WHY FACULTY?
• We established Faculty in 2014 because we thought that AI would be the most important technology of our time
• Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI
• You can read about our real-world impact here https://faculty.ai/impact
• We don’t chase hype cycles
• We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well

Требования

• You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch
• You possess strong Python skills and solid experience in software engineering best practices
• You bring hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security
• You've worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale
• You are comfortable with core ML concepts, including probability, statistics, and common learning techniques
• You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders
• You thrive in a fast-paced environment, and enjoy the autonomy to own scope, solve and delivery solutions
• OUR INTERVIEW PROCESS
• Talent Team Screen (30 minutes)
• Pair Programming Interview (90 minutes)
• System Design Interview (90 minutes)
• Commercial Interview (60 minutes)
• OUR RECRUITMENT ETHOS
• We aim to grow the best team - not the most similar one
• We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth
• And we know from experience that diverse teams deliver better work, relevant to the world in which we live
• We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact
• We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations
• Some of our standout benefits
• Unlimited Annual Leave Policy
• Enhanced parental leave
• Family-Friendly Flexibility & Flexible working
• Sanctus Coaching
• Hybrid Working

Условия

• Private healthcare and dental

Паспорт вакансии

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