Senior Machine Learning Engineer

Faculty; United States; Remote; USD 106,000 - 159,000; Full time

Job summary

Faculty is seeking a Senior Machine Learning Engineer to lead the development and deployment of production-grade ML systems for diverse clients. You’ll design, build, and scale AI software and infrastructure while meeting rigorous operational and ethical standards.

This cross-functional role requires engineering leadership, strong Python skills, cloud experience, and the ability to collaborate with stakeholders across teams. Occasional travel to client sites may be required.

Qualifications

• Extensive experience operationalising ML models in production.
• Strong software engineering with robust Python code.
• Hands-on with AWS/Azure/GCP and secure architectures.
• Experience with Docker and Kubernetes for scale.
• Ability to guide clients and stakeholders.

Responsibilities

• Lead technical scoping and architectural decisions for high-impact ML systems.
• Design and build production-grade ML software, tools, and scalable infrastructure.
• Define and implement best practices for deploying ML at scale across the business.
• Collaborate with engineers, data scientists, product managers, and commercial teams to solve client challenges.
• Act as a trusted technical advisor to customers and partners.
• Mentor and develop junior engineers, shaping the team's engineering culture.

Skills

TensorFlow

PyTorch

Python

Cloud platforms

Communication

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

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.

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. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.

Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.

AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.

About the team

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.

#LI-PRIO

About the role

As a Senior Machine Learning Engineer, we’ll look to you to lead development and deployment of cutting-edge AI systems for our diverse clients. You’ll design, build, and deploy scalable, production-grade ML software and infrastructure that meets rigorous operational and ethical standards.

This is an ambitious, cross-functional role requiring a blend of technical expertise, engineering leadership, and confident client-facing skills.

What you'll be doing:

• Leading technical scoping and architectural decisions for high-impact ML systems

• Designing and building production-grade ML software, tools, and scalable infrastructure

• Defining and implementing best practices and standards for deploying machine learning at scale across the business

• Collaborating with engineers, data scientists, product managers, and commercial teams to solve critical client challenges and leverage opportunities

• Acting as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies

• Mentoring and developing junior engineers, actively shaping our team's engineering culture and technical depth

Who we're looking for:

• You understand the full ML lifecycle and have significant experience operationalising models built with frameworks like TensorFlow or PyTorch

• You bring deep expertise in software engineering and strong Python skills, focusing on building robust, reusable systems

• You have demonstrable hands-on experience with cloud platforms (e.g., AWS, Azure, GCP), including architecture, security, and infrastructure

• You've extensive experience working with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale

• You thrive in fast-paced, high-growth environments, demonstrating ownership and autonomy in driving projects to completion

• You communicate exceptionally well, confidently guiding both technical teams and senior, non-technical stakeholders

The 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)

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.

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.