Faculty

Product Designer

• Leading the creation of complex, high-impact user interfaces that meet rigorous accessibility and inclusion standards.
• Planning, conducting, and overseeing autonomous user research activities to synthesize insights that drive strategic design decisions.
• Owning the development and delivery of wireframes, prototypes, and detailed designs for challenging problems.
• Taking responsibility for evolving the design system to meet project and organisational needs, and providing strategic guidance on implementation to engineers and peers.
• Facilitating cross-functional collaboration and effectively communicating design rationale to stakeholders, including senior leadership and clients.
• Leading iterative design processes, encouraging experimentation and validation efforts to continuously improve product usability and user satisfaction.

Senior Product Designer

Machine Learning Engineer

• 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

Senior Machine Learning Engineer

Data Scientist

• Serving as a technical authority on machine learning, statistics, and advanced data science methods to deliver innovative and impactful solutions.
• Leading the development of shared resources, frameworks, and best practices adopted across teams and the company.
• Driving the scoping and bid processes for large-scale, high-stakes projects, influencing client decisions with technical expertise.
• Owning a portfolio of work within a specific sector, applying expert knowledge to deliver exceptional value to clients.
• Leading and mentoring project teams, ensuring the successful delivery of high-value and complex projects.
• Contributing to thought leadership, publishing papers, and presenting at conferences to establish a unique voice in the data science community.

Principal Data Scientist

Account Manager

• Map and identify joint commercial opportunities
• Nurture relationships with key cloud partners
• Coordinate joint pursuit strategies
• Champion cloud partnerships internally
• Provide guidance to sales teams

Head of Partnerships

Cloud Engineer

• Build the backbone of applied artificial intelligence for customers by designing, building, and deploying robust, secure, and scalable cloud infrastructure that powers cutting-edge data and machine learning workflows.
• Partner with technical and non-technical stakeholders, from initial idea generation through to implementation and shipping.
• Enable Machine Learning Engineers and Data Scientists by contributing to internal best practices, standards, and reusable code repos.
• Proactively identify and recommend new ways customers can leverage cloud infrastructure to solve their key challenges.
• Create and maintain reusable, company-wide libraries and infrastructure-as-code.
• Research and integrate the best open-source technologies to enhance Faculty's infrastructure capabilities.

• Leading project teams that deliver bespoke algorithms and high-stakes AI solutions to clients across the sector.
• Conceiving the core data science approach and designing the associated robust software architecture for new engagements.
• Mentoring a small number of data scientists and supporting the professional growth of technical team members on projects.
• Partnering with commercial teams to build client relationships and shape project scope for technical feasibility.
• Contributing to Faculty’s thought leadership and reputation through delivering courses, public speaking, or open-source projects.
• Ensuring best practices are followed throughout the project lifecycle to guarantee high-quality, impactful delivery.

Senior Data Scientist

• Deliver bespoke algorithms to clients across different sectors
• Conceive the data science approach and design the software architecture
• Ensure best practices are followed
• Build strong relationships with clients and define project scope
• Collaborate with software engineers and designers from the product team

• Setting the technical direction for complex ML projects, balancing trade-offs, and guiding team priorities.
• Designing, implementing, and maintaining reliable, scalable ML/software systems and justifying key architectural decisions.
• Defining project problems, developing roadmaps, and overseeing delivery across multiple workstreams in often ill-defined, high-risk environments.
• Driving the development of shared resources and libraries across the organisation and guiding other engineers in contributing to them.
• Leading hiring processes, making informed selection decisions, and mentoring multiple individuals to foster team growth.
• Proactively developing and executing recommendations for adopting new technologies and changing our ways of working to stay ahead of the competition.
• Acting as a technical expert and coach for customers, accurately estimating large work-streams and defending rationale to stakeholders.

Lead Machine Learning Engineer

Manager

• Overseeing delivery of an end-to-end project portfolio focused on the education sector
• Ensuring high quality, timely completion, and managing commercial margins
• Forming and maintaining strong, trusted relationships with customers
• Proactively managing expectations and carefully controlling project scope
• Leading effective project meetings and ensuring clear, consistent communication
• Identifying risks early and leading teams to implement effective mitigating actions to ensure project success
• Developing compelling proposals and sales pitches to generate new leads
• Mentoring and developing project team members’ skills
• Advising clients on AI strategy and solutions

Senior Manager, Education

• Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse clients.
• You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices.
• 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.

• This is an exciting opportunity to join Faculty as the most senior data scientist in the Retail and Consumer business unit.
• Our Retail and Consumer experts are dedicated to helping clients in an industry which is being transformed by new technologies and evolving consumer expectations. Leveraging over a decade of experience in Applied AI, we combine exceptional technical and delivery expertise to empower businesses to adapt and thrive.
• You will help our excellent commercial team build strong relationships with clients, shaping the direction of both current and future projects. Particularly in the initial stages of commercial engagements, you will guide the process of defining the scope of projects to come with an emphasis on technical feasibility.
• You will play an important role in the development of others at Faculty by acting as the designated mentor of a small number of data scientists, and by supporting the professional growth of data scientists on the project team. The latter includes giving targeted support where needed, and providing step-up opportunities where helpful.
• You will actively contribute to the growth of this reputation by delivering courses to high-value clients, by talking at major conferences, by participating in external roundtables, or by contributing to large-scale open-source projects. You will also have the opportunity to teach on the fellowship about topics that range from basic statistics to reinforcement learning, and to mentor the fellows through their 6-week project.
• Because your work in data science will inform the development of our AI products, you will often collaborate with software engineers and designers from our dedicated product team.

Senior Data Scientist – Retail and Consumer

• Guide technical delivery of custom data science solutions
• Own end-to-end data science approach
• Design robust software architecture
• Partner with commercial teams to build relationships
• Articulate technical concepts to diverse audiences
• Manage and mentor data scientists
• Contribute to a high standard of performance
• Establish a differentiated data science vision
• Share latest technical advancements

Lead Data Scientist – Retail, Consumer

• You will help our excellent commercial team build strong relationships with clients, shaping the direction of both current and future projects. Particularly in the initial stages of commercial engagements, you will guide the process of defining the scope of projects to come with an emphasis on technical feasibility.
• Because your work in data science will inform the development of our AI products, you will often collaborate with software engineers and designers from our dedicated product team.
• Thanks to Faculty platform, you will have access to powerful computational resources, and you will enjoy the comforts of fast configuration, secure collaboration and easy deployment.

Data Scientist – Retail and Consumer

• Drive operational excellence whilst balancing strategic vision, forging deep relationships with customers and delivery partners.
• Be the operational backbone of our AI system implementations by planning and executing the work to meet customer requirements in partnership with technical teams across engineering, data science, and delivery.
• Build trust with stakeholders in global enterprises through delivery excellence and a deep understanding of how Frontier addresses their unique problems.
• Serve as the customers’ advocate within Faculty, providing feedback and insights to the product development team to enhance customer satisfaction.
• Create scalable delivery assets, from playbooks and education guides to process improvements that empower delivery partners and customers alike.
• Play an active role in account growth by scoping novel use cases and collaborating with business development team members on opportunities for Frontier.

Delivery Manager

Designer

• Lead design from discovery to deployment as a mid-weight Service Designer for Government and Public Sector projects.
• Conduct user research during the discovery phase of projects.
• Create user journey blueprints to explore and describe the service or operational environment.
• Build and test prototypes (digital and non-digital, e.g., policy ideas or processes).
• Work closely with clients and colleagues in multi-functional teams.
• Guide and train others in the organisation on service design methods and practices.
• Champion user-centred design across projects and the broader Faculty team.
• Operate autonomously and provide thought leadership in user research and product strategy.

Service Designer

• Implementing data-driven approaches, contributing to the design of scalable software architectures, and ensuring best practices are followed throughout development.
• Collaborate closely with our commercial team to help shape and deliver high-quality projects.
• Contribute to defining the technical scope in early stages of client engagements, ensuring proposed solutions are feasible and aligned with business objectives.
• Develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements.
• Support both technical, and non-technical stakeholders, to deploy ML to solve real-world problems.
• Building software and infrastructure that leverages Machine Learning.
• Creating reusable, scalable tools to enable better delivery of ML systems.
• Working with our customers to help understand their needs.
• Working with data scientists and engineers to develop best practices and new technologies.
• Implementing and developing Faculty’s view on what it means to operationalise ML software.
• Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems.
• Working with senior engineers to scope projects and design systems.
• Providing technical expertise to our customers.
• Technical Delivery

Full-stack Engineer

• Work closely with delivery teams responsible for visualising insights from data scientists
• Deliver solutions to Professional & Financial Services customers using AI and Machine Learning
• Create reliable, reusable and scalable frontend and backend to enable better delivery of AI systems
• Lead engineers in cross-functional teams of Data Scientists, Product Managers and Commercial staff to deliver technically sophisticated, high-impact systems
• Lead on the architecture and design of projects
• Offer leadership and management to more junior engineers on the team
• Be the go-to authority for engineering across the stack within your team
• Provide technical expertise to customers

Software Engineer

• At Faculty, we transform organisational performance through safe, impactful and human-centric AI.
• You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning.
• The work you do will help our customers solve a broad range of high-impact problems in the Defence and National Security arena.
• Building software and infrastructure that leverages Machine Learning;
• Creating reusable, scalable tools to enable better delivery of ML systems
• Working with our customers to help understand their needs
• Working with data scientists and engineers to develop best practices and new technologies; and
• Implementing and developing Faculty’s view on what it means to operationalise ML software.

At Faculty, we transform organisational performance through safe, impactful and human-centric AI.
With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme.
Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI.
You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. The work you do will help our customers solve a broad range of high-impact problems in the Defence and National Security arena.
You are engineering-focused, with a keen interest and working knowledge of operationalised machine learning. You have a desire to take cutting-edge ML applications into the real world. You will develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements. You will support both technical, and non-technical stakeholders, to deploy ML to solve real-world problems.

About Faculty: At Faculty, we transform organisational performance through safe, impactful and human-centric AI.
With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme.
Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI.
About the Role: Situated within our Applied AI consultancy; work across UK Defence, Government, Life Sciences, Energy, Banking and Retail; work may move between business areas depending on client requirements; need to be versatile and client-facing.
Requires eligibility for SC clearance and willingness to work up to three days per week on site with UK Defence customers; may require travel outside London base
What You'll Be Doing: Design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning.
Develop new methodologies and champion best practices for managing AI systems deployed at scale, supporting technical and non-technical stakeholders to deploy ML.
Responsible for engineering aspects of customer delivery projects: building software and infrastructure leveraging ML, creating reusable scalable tools, working with customers, working with data scientists and engineers, implementing Faculty’s view on operationalising ML software.
Key responsibilities include working in cross-functional teams, scoping projects/designing systems with senior engineers, providing technical expertise to customers, technical delivery