Lead AI Engineer
- Play a high impact role in driving our AI journey, helping intelligent org design become an everyday reality.
- Lead the technical delivery of, and help define, mission-critical AI initiatives - driving value through data enrichment and intelligent automation.
- Collaborate within a balanced, cross-functional team to design, develop, and deploy AI capabilities that enhance data quality and assist some of the world's biggest brands in making excellent decisions with regards to their organisation.
- Apply deep machine learning and software engineering expertise to prototype, evaluate, and productionise models across a range of use cases, including structured and unstructured data.
- Work closely with Product Managers to shape the roadmap, clarify expectations, and translate customer needs into intelligent, data-driven solutions.
- Build and evolve internal tooling and frameworks to accelerate AI experimentation, deployment, and monitoring - enabling others to move faster and safer.
- Contribute to the ongoing development of a scalable, maintainable, and ethical AI architecture, ensuring compliance with security and governance standards.
- Stay hands-on, setting the example while mentoring others and sharing knowledge to raise the technical bar across the team.
- Join us during an exciting, transformative phase, helping to shape our approach to intelligent systems as we simplify our platform and expand our product capabilities.
- Proven experience delivering machine learning or AI-powered features into production, ideally in a B2B SaaS or data-rich environment.
- Strong background in machine learning, data science, or applied AI, with hands-on experience in model development, evaluation, and deployment.
- Proficiency with relevant ML libraries and frameworks such as PyTorch, TensorFlow, scikit-learn, HuggingFace or similar
- Experience with modern ML tooling, such as MLflow, Jupyter, feature stores, and vector databases.
- Understanding of software engineering best practices including version control, testing, CI/CD, containerisation, and observability.
- Familiarity with MLOps principles - automated pipelines, model versioning, model monitoring, and reproducibility.
- Excellent communication skills with a collaborative mindset - you thrive on pairing with engineers, data scientists, and product managers.
- A growth mindset with a passion for continuous learning and improvement, and a willingness to explore new techniques, frameworks, or technologies.
- Hybrid working - 1+ days a week in the London office
- Wellbeing: Sanctus Coaching, Virtual fitness sessions, Wellbeing webinars, Annual Wellbeing day
- Subsidised Gym Membership
- Private Medical Insurance (including Dental and Vision) and Life Assurance
- 25 days holiday (increasing to 30 days at a rate of 1 extra day per year)
- Summer Fridays (half-day Fridays for the months of July and August)
- Employer pension contribution of 5% of your gross salary, if you contribute a minimum of 3%
- Season ticket Loan
- Cycle to Work Scheme
- Annual Discretionary Bonus
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