Senior AI / ML Engineer Leadership Role

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Location:

england, United Kingdom

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Other

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Yes

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Job Views:

4

Posted:

28.04.2025

Expiry Date:

12.06.2025

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Job Description:

Senior AI / ML Engineer Leadership Role – Start-Up – a new field of AI - Equity Consideration

Want to be part of a groundbreaking AI tech startup set to revolutionise user authentication to digital DNA? Our client leverages behavioural biometric interactions and powerful AI to create unique user profiles for seamless security.

We want to hear from you if you are experienced with taking LLM models into production and have any exposure to using large behavioural data.

Our client is a cutting-edge technology startup redefining authentication through groundbreaking behavioural biometrics and a new field of AI. Due to continued investment and ambitious growth plans, they seek a Senior AI / ML Engineer leader to play a pivotal role in AI Development.

We seek a Senior AI / ML Engineer Leader to develop and deploy AI models in a high-impact, hands-on role. As the most Senior Machine Learning Engineer, you will be instrumental in managing the entire lifecycle of ML models—from data exploration and development to deployment, monitoring, and ongoing enhancement.

We are looking for candidates with expertise in sensor-based data, large behaviour data, or behavioural biometrics. Ideal applicants will have experience analysing and interpreting complex behavioural data to drive insights and innovation. You will be a skilled professional with a strong history of turning prototypes into robust, production-ready solutions that drive meaningful impact.

Reporting to the Chief AI Officer, you will drive AI development, owning the processes that keep the machine learning models running smoothly in production. This involves developing and maintaining automated testing frameworks, optimising deployment workflows, and establishing robust version control systems designed for ML operations. You have a strong track record of successfully deploying models, transforming prototypes into scalable and reliable production systems.

You should be comfortable navigating ambiguity while balancing experimentation with delivery. If you thrive in an environment where you can explore new ideas while getting things done, this could be the ideal role for you

This is your chance to join the early stages of growth and play a key role in shaping the future before they scale globally. Don't miss the opportunity to be part of the original team driving this innovation forward! Why not join during the seed growth and funding stage for a chance at early equity consideration

Key Responsibilities of the Senior AI / ML Engineer Leader

• Architect and optimise scalable data pipelines for seamless data cleaning, analysis, and modelling.
• Experiment with large language models (LLMs) and emerging AI techniques and apply them effectively.
• Work with complex, real-world datasets to ensure that the models are robust. Work with complex, real-world datasets to ensure that the models are robust.
• Develop, rigorously test, and deploy machine learning models built to scale and perform reliably in production.
• Continuously monitor and refine model performance, proactively addressing data drift and evolving business needs.
• Inspire and mentor junior engineers, fostering growth, technical excellence, and adherence to best practices.
• Collaborate across teams, translating insights into strategic decisions that drive real business impact.
• Champion a culture of innovation and accountability, leading open discussions on ethics, transparency, and data privacy.
• Stay at the forefront of AI research and translate insights into real-world applications

Key Skills & Experience Required for Senior AI / ML Engineer Leader

• Expertise in sensor-based data, large behaviour data models, or behavioural biometrics (Mandatory)
• Demonstrated success in developing and deploying machine learning models from prototype to large-scale production.
• LLM experience - optimising and serving LLMs for real-world applications
• Expertise with MLOps tools and practices (e.g., Docker, CI/CD pipelines, monitoring frameworks).
• Strong proficiency in Python and libraries like Pandas, NumPy, and scikit-learn, with familiarity in frameworks like TensorFlow or PyTorch being a plus
• Cloud experience—AWS preferred - including deploying and managing models in cloud environments (will still consider GCP / Azure)
• Curious and pragmatic mindset—comfortable exploring new ideas while delivering results
• Strong, clear communication skills—ability to explain ideas concisely and get to the point
• Experience working with real-world, behavioural, or sensor-based data is a plus