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Data & AnalyticsHybrid

Senior Machine Learning Engineer

Faculty · Hybrid

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Last seen by MeritLog September 9, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Faculty's Ashby job board and last checked it on September 9, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model
Hybrid
Salary
Not listed by source
Location
UK - London
Occupation
Computer Systems Engineers/Architects(O*NET 15-1299.08)
Company website
faculty.ai

Hiring context

How this role compares at Faculty

Faculty has 72 live roles in MeritLog’s catalog across 3 job families, and 48 of them are in data & analytics. 0 of those listings publish a pay range, a disclosure rate of 0%.

Faculty concentrates this hiring in:

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd do

  • 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
  • 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
  • Talent Team Screen (30 minutes)
  • Pair Programming Interview (90 minutes)
  • System Design Interview (90 minutes)
  • Commercial Interview (60 minutes)

Parsed by MeritLog from the employer’s own posting. The full description follows below.

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 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. 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   Bringing medicine to patients is complex, expensive and high-risk. Faculty’s Life Science’s team is concentrated on building AI solutions which optimise the research and commercialisation of life-changing therapies. We partner with major pharma firms, academic research centres and MedTech start-ups to design and deliver solutions which address critical healthcare challenges, and help to democratise health for all.     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. 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.

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