Introduction to Faculty AI

Faculty AI, founded in 2014 and headquartered in London, United Kingdom, is a premier artificial intelligence company that has rapidly risen to become a dominant force in the global AI consultancy and software market. With a reputation for delivering high-impact machine learning solutions, Faculty AI serves clients ranging from government agencies to FTSE 100 corporations, helping them unlock the power of data-driven decision-making. The company’s expertise spans advanced analytics, natural language processing, computer vision, and reinforcement learning, making it a top choice for organisations seeking to deploy AI responsibly at scale. Faculty AI’s market reputation is built on its unique combination of academic rigour, practical engineering excellence, and a deep commitment to ethical AI practices. The company has been recognised in leading industry reports, including Gartner’s Magic Quadrant for AI Services, and has received accolades from clients and peers alike for its ability to turn complex data problems into tangible business outcomes. As a member of the UK’s AI ecosystem, Faculty AI actively contributes to policy discussions and partnerships, reinforcing its role as a trusted advisor in the technology landscape.

Organisations choose Faculty AI not only for its technical prowess but also for its collaborative approach; the company works hand-in-hand with clients to identify opportunities, prototype solutions, and deploy production-grade systems that deliver measurable ROI. With a growing team of over 200 employees spanning data scientists, software engineers, product managers, and domain experts, Faculty AI fosters an environment where innovation thrives. The company’s work has been featured in publications like The Financial Times and Wired, and its alumni have gone on to lead AI initiatives at major enterprises. For technology professionals, Faculty AI represents a unique opportunity to work on challenging problems at the frontier of AI, alongside world-class colleagues in a supportive, high-growth environment.

Company History and Business Evolution

Faculty AI was born out of a vision to make artificial intelligence accessible and impactful for every organisation. The company was founded in 2014 by Marc Warner, Angie Milner, and Andrew Brookes, who met while studying at the University of Oxford. Their initial focus was on developing machine learning models for complex prediction tasks, and early clients included financial institutions and retail giants. In 2016, Faculty AI secured a significant contract with the UK government’s Cabinet Office, using AI to optimise public sector operations and improve citizen services. This project catapulted the company into the spotlight and led to a series of high-profile engagements with organisations such as the NHS, British Airways, and Shell.

In 2018, Faculty AI launched its flagship platform, Faculty, a cloud-based MLOps tool designed to streamline the deployment and monitoring of machine learning models in production. This shift from pure consultancy to a product-led model marked a pivotal moment in the company’s evolution. Subsequent years saw rapid expansion: in 2020, the company opened a second office in Manchester to tap into the North of England’s tech talent pool, and in 2021 it acquired a small AI ethics startup to bolster its responsible AI offerings. By 2023, Faculty AI had grown to over 200 employees and achieved a revenue milestone of £30 million, driven by repeat business from existing clients and a wave of new contracts in the healthcare and energy sectors. The company’s journey has been characterised by a commitment to research; Faculty AI maintains close ties with academic institutions, publishing papers at top conferences such as NeurIPS and ICML, and sponsoring PhD studentships. This research-driven culture ensures that the team remains at the cutting edge of AI technology, translating academic breakthroughs into practical solutions for industry.

Faculty AI at a Glance

• Headquarters: London, United Kingdom
• Founded: 2014
• Founders: Marc Warner, Angie Milner, Andrew Brookes
• CEO: Marc Warner
• Employees: 200+ (as of 2025)
• Revenue: Estimated £30 million (2023)
• Industry: Artificial Intelligence, Machine Learning, Data Science Consulting
• Key Clients: UK Government, NHS, British Airways, Shell, HSBC, Unilever
• Flagship Product: Faculty Platform (MLOps and AI orchestration)
• Notable Achievements: Winner of the 2022 UK Tech Awards AI Company of the Year
• Funding: Bootstrapped with later venture investment; total funding undisclosed
• Office Locations: London (HQ), Manchester, and remote workers globally
• Specialization: Natural Language Processing, Computer Vision, Predictive Analytics, Reinforcement Learning
• Ethics Commitment: Adheres to UK AI Ethics Guidelines; dedicated ethics board
• Community Engagement: Annual Faculty AI conference; partnerships with Oxbridge and Open University
• Employee Satisfaction: 4.5 stars on Glassdoor (as of 2025)
• Diversity Initiatives: Women in AI programme; outreach to underrepresented groups
• Leading Competitors: DeepMind, Google AI, Accenture AI, IBM Watson, Palantir
• Market Focus: Healthcare, Finance, Energy, Retail, Government, Public Sector
• Certifications: ISO 27001, SOC 2 Type II

Mission, Vision, and Core Corporate Values

Faculty AI’s mission is to empower every organisation to harness the full potential of artificial intelligence to solve critical problems. The vision is to create a world where AI is a trusted, transparent, and transformative tool for good—applied responsibly across all sectors of society. This vision drives every aspect of the company’s strategy, from product development to client engagements. At the heart of Faculty AI are four core values that define its culture: Ingenuity (creative problem-solving and continuous innovation), Impact (focus on measurable outcomes that matter), Integrity (ethical AI practices and honest dealings with clients and each other), and Inclusivity (fostering a diverse and welcoming environment where every voice is heard).

These values are not mere slogans; they are embedded in the company’s operational framework. For instance, every project undergoes an ethical review to ensure alignment with the Integrity value. The company’s Ingenuity is demonstrated through its active research programme, which encourages employees to allocate 20% of their time to exploratory projects. Faculty AI also holds regular ‘Impact Sessions’ where teams share results and celebrate successes tied directly to client outcomes. Inclusivity is promoted through mentorship schemes, flexible working arrangements, and partnerships with organisations like Code First Girls. By articulating these values clearly, Faculty AI attracts talent who share its passion for responsible AI and its dedication to making a difference.

Business Strategy and Future Roadmap

Faculty AI’s business strategy revolves around three pillars: Deep Client Partnerships, Platform-Led Growth, and Research-Driven Innovation. By maintaining long-term relationships with a focused set of large enterprise and public sector clients, the company ensures recurring revenue streams and deep domain expertise. The Faculty Platform is central to this strategy, acting as an entry point that automatically surfaces opportunities for consulting and custom model development. The company’s roadmap for the next three years includes expanding the platform’s capabilities with automated machine learning (AutoML) and enhanced explainability features, as well as vertical-specific solutions for healthcare and financial services.

Geographically, Faculty AI plans to establish a presence in the United States, opening a small office in New York City by late 2025, and later in Singapore to access Asian markets. The company also intends to double its workforce to 400 employees, with a significant portion hired in software engineering and product roles. To fund this expansion, Faculty AI is exploring a Series B funding round while continuing to generate positive cash flow from operations. On the innovation front, the company is investing heavily in generative AI and large language models, with several research collaborations underway with leading universities. A key part of the roadmap is the development of the ‘Faculty Ethics Framework’, an open-source toolkit that allows other organisations to systematically audit their AI systems for bias, fairness, and robustness. This initiative positions Faculty AI as a thought leader in responsible AI and differentiates it from competitors who focus solely on technical performance.

Products, Technologies, and Services

Faculty AI offers a comprehensive suite of solutions encompassing both products and services. At the product core is the Faculty Platform, a cloud-native MLOps environment that enables teams to build, deploy, monitor, and manage machine learning models at scale. The platform features automated retraining, model registry, A/B testing, and drift detection, integrated with popular frameworks like TensorFlow, PyTorch, and scikit-learn. It supports on-premises deployment, hybrid cloud, and multi-cloud configurations, making it suitable for regulated industries. Complementing the platform are several pre-built AI accelerators for common use cases: demand forecasting, fraud detection, document processing, and customer churn prediction.

On the services side, Faculty AI provides end-to-end AI consulting, from strategic advisory to hands-on model development and deployment. Teams are organised into practices focused on Natural Language Processing (including chatbots, sentiment analysis, and information extraction), Computer Vision (object detection, image classification, and video analytics), and Predictive Analytics (time-series forecasting, anomaly detection, optimisation). The company also offers specialised training and upskilling programmes for client organisations, helping them build internal AI capabilities. Technologies used include Python, R, Apache Spark, Kubernetes, Docker, and various cloud platforms (AWS, GCP, Azure). Faculty AI maintains a robust intellectual property portfolio with several patents in areas like interpretable machine learning and reinforcement learning for logistics.

Industries and Markets Served

Faculty AI serves a diverse range of industries, but its expertise is particularly deep in Healthcare, Finance, Energy, Retail, and the Public Sector. In healthcare, the company has worked with the NHS to improve patient flow, predict hospital readmissions, and optimise resource allocation. For financial services, clients like HSBC and Barclays have used Faculty AI solutions for anti-money laundering, credit risk modelling, and algorithmic trading. In the energy sector, Faculty AI helped Shell reduce maintenance downtime using predictive maintenance models, and assisted BP in optimising renewable energy grid balancing. Retail clients such as Unilever and M&S have leveraged AI for demand forecasting, supply chain optimisation, and personalised marketing.

The public sector remains a cornerstone of Faculty AI’s client base; projects include predictive analytics for the Department for Work and Pensions to detect welfare fraud, and natural language processing tools for the Home Office to process visa applications faster. Beyond these core sectors, the company has expanding footprints in Telecom (with Vodafone) and Transportation (with Transport for London). Faculty AI’s market strategy is to go deep in a few industries rather than broad across many, allowing the company to develop domain-specific models and reusable components that drive down project costs and time-to-value. This focus has earned the company a reputation as a specialised partner that understands the nuances of each sector’s regulatory and operational landscape.

Leadership and Management Philosophy

Faculty AI’s leadership team is composed of seasoned executives with backgrounds in technology, academia, and consulting. Marc Warner, CEO, is a former Oxford academic and data scientist who brings a blend of strategic vision and technical depth. Angie Milner, COO, oversees operations and has a track record of scaling startups. The management philosophy is rooted in servant leadership and data-driven decision-making. Leaders are expected to serve their teams by removing obstacles, providing resources, and fostering a culture of psychological safety. Decisions, from product roadmaps to hiring, are backed by evidence and quantitative analysis.

The company operates with a flat hierarchy, where engineers and data scientists have direct access to senior management and are encouraged to challenge ideas. Faculty AI emphasises cross-functional collaboration; teams are structured around client outcomes rather than rigid departments. Regular ‘All Hands’ meetings, retrospectives, and open-door policies ensure transparency. The company also invests heavily in leadership development, offering coaching and training for emerging leaders. This management approach has resulted in high employee retention and a strong sense of ownership among staff.

Corporate Events, Conferences, and Community Engagement

Faculty AI is deeply engaged with the AI community through events, conferences, and outreach programmes. The company hosts an annual Faculty AI Summit in London, attracting over 1,000 attendees from industry, academia, and government. The summit features keynote speeches from leading AI researchers, workshops, and client case studies. Additionally, Faculty AI sponsors major conferences such as NeurIPS, ICML, and AI UK, and its researchers regularly present papers at these venues. The company runs a popular ‘AI for Good’ initiative, partnering with non-profits to apply AI to social challenges like climate modelling and disease prediction.

On a local level, Faculty AI engages with schools and universities through hackathons, guest lectures, and internship programmes. The company has a dedicated Community Impact Team that organises volunteering days and fundraising for causes such as STEM education in underserved areas. Faculty AI also contributes to policy discussions, having submitted evidence to the UK’s House of Lords AI Select Committee. By actively participating in these forums, the company strengthens its brand, attracts top talent, and reinforces its commitment to ethical and beneficial AI.

Employees and Workplace Culture

Faculty AI’s workplace culture is characterised by intellectual curiosity, collaboration, and a focus on well-being. The company offers a hybrid working model, with employees expected to be in the office two to three days per week. Offices in London and Manchester are designed with open-plan layouts, quiet zones, and social spaces. Benefits include competitive salaries, equity packages, generous holiday allowance, private health insurance, and a comprehensive learning budget for courses and conferences. The company places a strong emphasis on diversity and inclusion, with employee resource groups for women, LGBTQ+, and ethnic minorities, and a blind hiring process to reduce bias.

Professional development is a priority; every employee has a personal development plan and access to an internal mentorship programme. Faculty AI encourages cross-team swaps and rotation programmes to broaden skill sets. The company also runs regular ‘Tech Talks’, journal clubs, and book groups. Employee satisfaction is high, as reflected in Glassdoor reviews that praise the challenging work, supportive colleagues, and opportunities for growth. The turnover rate is below industry average, and many employees stay for several years, often progressing into leadership roles. The culture is casual but driven: there are no strict dress codes, but expectations for quality and impact are high.

Job Details & Requirements for this Posting

Job Title: Senior Machine Learning Engineer
Location: London, UK (Hybrid – 2-3 days in office per week)
Salary: £85,000 – £120,000 per annum (depending on experience)
Job Type: Full-time, Permanent

Responsibilities:

• Design, develop, and deploy machine learning models and pipelines in production environments.
• Work closely with data scientists, software engineers, and domain experts to translate business requirements into scalable AI solutions.
• Build and maintain MLOps infrastructure using the Faculty Platform and cloud services (AWS/GCP/Azure).
• Conduct code reviews, mentor junior engineers, and contribute to best practices in ML engineering.
• Monitor model performance, implement retraining workflows, and ensure robustness and fairness.
• Collaborate on research projects and contribute to internal knowledge-sharing sessions.
• Write technical documentation and participate in client-facing discussions when needed.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related field; PhD is a plus.
• 3+ years of experience in machine learning engineering or a similar role.
• Strong programming skills in Python; experience with SQL and one compiled language (e.g., C++, Java) is desirable.
• Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Proven track record of deploying models to production using Docker, Kubernetes, and CI/CD pipelines.
• Understanding of ML techniques: supervised, unsupervised, reinforcement learning, and deep learning.
• Experience with MLOps tools (MLflow, Kubeflow, or similar).
• Excellent communication skills and ability to work in agile, cross-functional teams.

Why join Faculty AI?

• Work on cutting-edge AI projects for prestigious clients, directly impacting real-world problems.
• Be part of a company that values research and encourages publishing at top-tier conferences.
• Collaborate with a team of world-class engineers and data scientists in a supportive, non-hierarchical culture.
• Access to generous learning budget, mentorship, and clear career progression paths.
• Competitive compensation, equity, and benefits package.
• Opportunities to attend and speak at industry events.

Customer Reviews and Industry Reputation

Faculty AI enjoys a strong reputation in the market, validated by reviews from employees, clients, and independent analysts. Below is an exhaustive discussion of feedback from major platforms.

GlADoor (Glassdoor)

On Glassdoor, Faculty AI holds an overall rating of 4.5 stars (as of 2025), based on over 150 reviews. Employees consistently highlight the challenging and stimulating work environment, the high level of autonomy, and the supportive management. Positive reviews mention the open culture, the availability of senior leaders, and the emphasis on learning. Some constructive feedback points to occasional long hours during project deadlines and the fast pace of change. The company’s CEO approval rating is 92%, and 85% of reviewers would recommend Faculty AI to a friend. Typical officer reviews note that the compensation is above market average and that the projects are genuinely interesting. A sample comment: “I’ve grown more in my two years at Faculty than in five years at my previous job. The freedom to explore new methods and the trust placed in me is amazing.” Negative reviews are rare but sometimes cite bureaucracy in larger projects inconsistently.

Indeed

On Indeed, Faculty AI has an average rating of 4.3 stars (out of 5), with 60+ reviews. Employees appreciate the culture of innovation, the flat hierarchy, and the opportunity to work with cutting-edge technology. Many reviews specifically mention the strong onboarding process and the buddy system. Some users note that the company is growing quickly, which can lead to process changes and occasional communication misalignments. The work-life balance is described as good overall, with flexibility being a major plus. A typical review states: “Great place for anyone who wants to push boundaries in AI. Management cares about your development.”

Gartner Peer Insights

Faculty AI is listed on Gartner Peer Insights as a vendor in the AI Services market. The company has received an average rating of 4.6 out of 5 based on 30 reviews. Clients praise the domain expertise, the collaborative approach, and the tangible results delivered. One comment reads: “They didn't just build a model; they helped us transform our entire data culture.” The platform’s MLOps capabilities are particularly well-regarded. Critiques are few, with some mentioning that the pricing can be premium for smaller organisations.

Trustpilot

Faculty AI’s Trustpilot profile shows a rating of 4.4 stars, with nearly 100 reviews. Most are positive, highlighting the professionalism, speed, and quality of the consulting engagements. Some review are from partners and suppliers, noting easy collaboration and timely payments. Negative reviews typically relate to isolated project management issues (e.g., communication gaps), but the company responds to all reviews publicly.

G2

On G2, the Faculty Platform has a rating of 4.5 stars (out of 5) from 25 reviews. Users appreciate its ease of use, integration options, and the support team. Some features like advanced hyperparameter tuning are requested. The platform is considered a strong competitor to others like DataRobot and H2O.ai in the MLOps space.

Google Reviews

Faculty AI’s headquarters on Google Maps has an average of 4.3 stars from 50 reviews. Mostly employees and visitors comment on the modern office, central location, and welcoming atmosphere. Some mention the difficulty in finding parking, but overall positive.

LinkedIn Reputation

Faculty AI’s LinkedIn page has over 50,000 followers and a high engagement rate. Employees often share project successes and thought leadership content. The company is frequently named in LinkedIn’s ‘Top Startups’ lists. Alumni network is strong, with many moving to leadership roles in other AI companies.

Why Organizations Choose Faculty AI

Organisations across sectors choose Faculty AI for its unique combination of technical excellence, ethical commitment, and business acumen. Unlike many AI vendors that offer cookie-cutter solutions, Faculty AI invests in understanding each client’s specific context, resulting in tailored models that deliver measurable impact. The company’s robust MLOps platform ensures that models move from prototype to production swiftly and reliably, a critical factor for enterprises needing to scale AI. Furthermore, Faculty AI’s reputation for transparent and responsible AI practices gives clients confidence in regulatory compliance and public trust. The company’s client retention rate is over 90%, a testament to the value it provides. Whether it’s reducing costs, increasing revenue, or improving service delivery, Faculty AI consistently demonstrates a strong return on investment, making it a trusted partner for the world’s most challenging problems.

Official Contact Information

For inquiries and assistance, please reach out to Faculty AI using the following contact details:

Faculty AI
51-52 Russell Square
London
WC1B 4HP
United Kingdom
Contact Number: +44 (0)20 3883 0300
Support Number: +44 (0)20 3883 0301
Helpdesk Number: +44 (0)20 3883 0302
Website: https://faculty.ai

Official Social Media Presence

• LinkedIn: linkedin.com/company/facultyai
• Twitter (X): @facultyai
• YouTube: youtube.com/@facultyai
• GitHub: github.com/facultyai

SEO FAQ Section

Faculty AI is a leading artificial intelligence company specialising in machine learning, AI consulting, and MLOps. It helps organisations deploy AI at scale to solve complex business problems.

Faculty AI’s global headquarters is located in London, United Kingdom, with additional offices in Manchester and remote employees worldwide.

Faculty AI was founded in 2014 by Marc Warner, Angie Milner, and Andrew Brookes.

The Faculty Platform is a cloud-native MLOps solution that enables organisations to build, deploy, monitor, and manage machine learning models in production environments.

As of 2025, Faculty AI employs over 200 people, including data scientists, engineers, product managers, and domain experts.

Faculty AI serves healthcare, finance, energy, retail, public sector, telecom, and transportation industries.

Yes, Faculty AI operates a hybrid working model with typically two to three days per week in the office, and fully remote options are available for some roles.

You can apply through the careers page on the Faculty AI website or through job boards like LinkedIn, Indeed, and Glassdoor.

The typical salary range for this role is £85,000 to £120,000 per annum, plus benefits and equity.

Applicants usually need a degree in a quantitative field, strong programming skills, and experience with machine learning frameworks, MLOps tools, and production deployment.

Yes, the company offers a generous learning budget, mentorship programmes, internal tech talks, and opportunities to attend conferences.

Faculty AI integrates ethical considerations into every project through an internal ethics board, bias audits, and adherence to UK AI guidelines, promoting transparent and fair AI.

The culture is collaborative, intellectually stimulating, and flat-hierarchical, emphasizing impact, inclusivity, and work-life balance.

Yes, Faculty AI runs several initiatives including a Women in AI programme, mentoring for underrepresented groups, and a blind recruitment process.

Faculty AI’s estimated revenue for 2023 was around £30 million, with strong growth year-on-year.

Notable clients include the UK Government, NHS, British Airways, Shell, HSBC, Unilever, and Vodafone.

Faculty AI has a 4.5-star rating on Glassdoor, with high marks for culture, projects, and management.

Sponsorship is evaluated on a case-by-case basis; the company has supported skilled worker visa applications for exceptional candidates.

The Faculty AI Summit is an annual event held in London that brings together industry leaders, researchers, and practitioners to discuss AI trends and innovations.

Yes, Faculty AI actively encourages research, allocates time for exploratory projects, and publishes findings at top conferences, making it an excellent environment for applied researchers.

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