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- Tasks: Transform complex behavioural data into intelligent, scalable systems and deploy machine learning models.
- Company: Join a vibrant early tech start-up in Manchester focused on AI and behavioural biometrics.
- Benefits: Enjoy hybrid working, competitive salary, and potential equity consideration as the company grows.
- Why this job: Be part of an innovative team shaping the future of AI with real-world applications.
- Qualifications: 2+ years in AI/ML engineering, proficiency in Python, and experience with cloud platforms.
- Other info: Opportunity to join during seed growth stage and make a significant impact.
The predicted salary is between 40000 - 64000 £ per year.
Location: Manchester - Hybrid / Home working
Job Type: Full-time
Salary: £50,000 - £80,000 base
We are looking for a mid-level AI / Machine Learning Engineer to join a vibrant early tech start-up in Manchester. Do you love turning machine learning models into intelligent, real-world applications? This is your chance to join a cutting-edge start-up team shaping the brainpower behind Behavioural biometrics and AI. Our client leverages behavioural biometric interactions and powerful AI to create unique user profiles for seamless security.
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. 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?
Due to recent investments and ambitious growth plans, they are looking for an AI Engineer to join the team.
The Role:
- As an AI / ML Engineer, you’ll transform complex behavioural data into responsive, intelligent, and scalable systems that think and adapt in real time.
- Architect and deploy machine learning models from idea to production.
- Build robust APIs and microservices to serve AI models at scale.
- Integrate behavioural intelligence models across cloud platforms (AWS, GCP, Azure).
- Set up end-to-end MLOps pipelines: monitoring, retraining, and automation.
- Collaborate with cross-functional teams to align tech with user-centric product design.
What We’re Looking For:
- ~2+ years in AI/ML engineering or backend software roles with ML components.
- ~Proficiency in Python and frameworks like PyTorch/TensorFlow, Scikit-learn.
- ~Experience deploying models with Docker, Kubernetes, or serverless architectures.
- ~Solid grasp of MLOps workflows, versioning, and cloud automation.
- ~Strong foundations in algorithms, data structures, and system design.
- ~Bonus: Familiarity with behavioural biometrics, sensor-based or time series data.
- ~An entrepreneurial mindset—curious, autonomous, and passionate about human-centred AI.
Full Time Engineer employer: 55 Exec Search
Contact Detail:
55 Exec Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Full Time Engineer
✨Tip Number 1
Network with professionals in the AI and machine learning field, especially those who have experience in behavioural biometrics. Attend local meetups or online webinars to connect with potential colleagues and learn more about the industry.
✨Tip Number 2
Showcase your projects related to AI/ML on platforms like GitHub. Having a portfolio of your work can demonstrate your skills in deploying models and working with complex data, which is crucial for this role.
✨Tip Number 3
Familiarise yourself with the latest trends in behavioural biometrics and AI technologies. Being knowledgeable about current advancements can help you stand out during interviews and discussions with the team.
✨Tip Number 4
Prepare to discuss your experience with MLOps workflows and cloud platforms like AWS, GCP, or Azure. Being able to articulate your hands-on experience with these tools will be beneficial in demonstrating your fit for the role.
We think you need these skills to ace Full Time Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI and machine learning. Focus on projects where you've transformed complex data into actionable insights, especially if they relate to behavioural biometrics or sensor-based data.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your skills align with the company's mission. Mention specific technologies you’ve worked with, like Python, PyTorch, or TensorFlow, and how you can contribute to their innovative projects.
Showcase Your Projects: If you have any personal or professional projects that demonstrate your ability to deploy machine learning models or work with MLOps, include them in your application. This could be through links to GitHub repositories or detailed descriptions in your CV.
Highlight Soft Skills: Since the role involves collaboration with cross-functional teams, emphasise your communication and teamwork skills. Provide examples of how you've successfully worked in teams to achieve project goals, particularly in tech environments.
How to prepare for a job interview at 55 Exec Search
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and frameworks like PyTorch or TensorFlow. Bring examples of projects where you've deployed machine learning models, especially using Docker or Kubernetes.
✨Demonstrate Problem-Solving Abilities
Expect technical questions that assess your understanding of algorithms, data structures, and system design. Practice explaining your thought process when tackling complex problems, as this will showcase your analytical skills.
✨Highlight Your Experience with MLOps
Discuss your familiarity with MLOps workflows, including monitoring and retraining models. Be ready to explain how you've set up automation in previous roles, as this is crucial for the position.
✨Emphasise Your Entrepreneurial Mindset
The start-up environment values curiosity and autonomy. Share examples of how you've taken initiative in past projects or how you've contributed to user-centric designs, demonstrating your passion for human-centred AI.
