ABOUT THE ROLE
Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse clients.
You will bridge the gap between AI research and real-world impact by building scalable, production-grade machine learning systems. Partnering with clients and cross-functional teams, you will champion technical feasibility, ensure seamless delivery, and collaborate with Frontier Labs to reinforce our leadership in practical, high-stakes AI safety.
WHAT YOU'LL BE DOING
Building and deploying production-grade ML software, tools, and infrastructure.
Creating reusable, scalable solutions that accelerate the delivery of ML systems and capability testing of Frontier AI models.
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.
WHO WE'RE LOOKING FOR
You are comfortable building LLM applications, and are familiar with multi-agent harness tooling and AI Safety evaluation procedures.
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 understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.
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
1. Talent Team Screen (30 minutes)
2. Pair Programming Interview (90 minutes)
3. System Design Interview (90 minutes)
4. Commercial Interview (60 minutes)
#LI-PRIO
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.
If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.
A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
