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- Tasks: Design and deploy advanced AI models while mentoring junior engineers.
- Company: Join a cutting-edge firm revolutionising digital security with AI and behavioural biometrics.
- Benefits: Enjoy hybrid working, competitive salary, and early equity opportunities.
- Why this job: Be part of an innovative team making a real-world impact in AI technology.
- Qualifications: 4+ years in AI/ML, strong academic background, and proficiency in Python required.
- Other info: Must be eligible for UK Government Security Clearance.
The predicted salary is between 60000 - 84000 £ per year.
Location: Manchester – Hybrid 3 days in the office / Home working
Salary: £75,000 - £100,000 base (dependent on experience)
We’re looking for candidates with strong experience in Computational Linguistics to help build and refine intelligent language technologies, combining linguistic expertise with technical skills to drive innovation in NLP and AI applications. Our client uses behavioural biometric interactions and advanced AI to create unique digital user identities, enabling seamless, intelligent security systems that adapt in real time. With ambitious growth plans on the horizon, this is the ideal time to get in early and make a defining impact.
As a senior member of this growing team, you’ll help architect and scale intelligent systems that analyse complex behavioural data (e.g. sensor, motion, touch, or biometric patterns). You'll work across the full lifecycle, from R&D and prototyping to robust deployment, and help define the technical strategy as the company prepares to scale.
Key Responsibilities:- Design, train, and deploy advanced machine learning and behavioural intelligence models.
- Lead the transition of prototypes into scalable, cloud-native production systems.
- Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps).
- Work with large-scale time series and behavioural data from diverse sensors.
- Contribute to strategic technical decisions and mentor junior engineers.
- Collaborate cross-functionally with product, UX, and leadership to align AI capabilities with real-world applications.
- MANDATORY – Must be eligible for UK Government Security Clearance.
- 4+ years in AI/ML engineering or data science roles, ideally within high-growth or research-driven environments.
- Strong academic background in Machine Learning, Computer Science, Applied Maths, Computational linguistics or a related field (MSc/PhD strongly preferred).
- Any candidates with exposure to computational linguistics are highly desirable, either from a research academic or commercial perspective.
- Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn.
- Experience deploying AI solutions into production environments using AWS/GCP/Azure.
- Hands-on with MLOps, CI/CD for ML, and model performance monitoring.
- A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus.
- A passion for human-centred AI, innovation, and applying research in real-world contexts.
Contact Detail:
55 Exec Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - (Senior AI/ML Engineer)
✨Tip Number 1
Make sure to showcase your experience with AI/ML engineering and data science in your conversations. Highlight specific projects where you've built and deployed AI systems, especially those that involved behavioural biometrics or computational linguistics.
✨Tip Number 2
Network with professionals in the field of AI and machine learning. Attend relevant meetups or conferences in Manchester to connect with potential colleagues or mentors who can provide insights into the company culture and expectations.
✨Tip Number 3
Familiarise yourself with the latest trends and technologies in NLP and AI applications. Being able to discuss recent advancements or case studies during interviews can demonstrate your passion and knowledge in the field.
✨Tip Number 4
Prepare to discuss your approach to mentoring junior engineers and collaborating cross-functionally. This role requires strong leadership skills, so be ready to share examples of how you've successfully guided teams or worked with diverse stakeholders.
We think you need these skills to ace Data Scientist - (Senior AI/ML Engineer)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI/ML engineering and data science. Emphasise any projects related to computational linguistics, behavioural biometrics, or large-scale data analysis, as these are key areas for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for human-centred AI and innovation. Discuss how your background aligns with the company's goals and mention specific experiences that demonstrate your ability to transition prototypes into scalable systems.
Showcase Relevant Projects: Include a portfolio or links to relevant projects that showcase your skills in deploying AI solutions and working with ML libraries like TensorFlow or PyTorch. Highlight any experience you have with MLOps and cloud platforms such as AWS or GCP.
Prepare for Technical Questions: Anticipate technical questions related to machine learning models, data pipelines, and behavioural data analysis. Be ready to discuss your approach to problem-solving and how you've contributed to strategic decisions in previous roles.
How to prepare for a job interview at 55 Exec Search
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and ML libraries like Hugging Face, PyTorch, and TensorFlow. Bring examples of projects where you've deployed AI solutions into production, as this will demonstrate your hands-on expertise.
✨Highlight Your Academic Background
Since a strong academic foundation is crucial for this role, be ready to talk about your MSc or PhD work. Discuss any research related to computational linguistics or machine learning that showcases your depth of knowledge.
✨Demonstrate Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you overcame them. This could include transitioning prototypes into scalable systems or working with complex behavioural data.
✨Express Your Passion for Human-Centred AI
Convey your enthusiasm for applying AI in real-world contexts, especially in relation to behavioural biometrics and human-computer interaction. Share any relevant experiences that highlight your commitment to innovation in this area.
