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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 behavioural biometrics and AI.
- 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 and make a meaningful impact.
- Qualifications: 2+ years in AI/ML engineering, proficiency in Python, and experience with MLOps workflows.
- Other info: Ideal for those with an entrepreneurial mindset and passion for human-centred AI.
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!
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.
Contact Detail:
55 Exec Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer (m/f/d)
✨Tip Number 1
Familiarise yourself with the latest trends in behavioural biometrics and AI. Understanding the current landscape will not only help you during interviews but also show your genuine interest in the field.
✨Tip Number 2
Network with professionals in the AI and machine learning community, especially those involved in start-ups. Attend meetups or webinars to connect with potential colleagues and learn about their experiences.
✨Tip Number 3
Showcase your practical experience by working on personal projects or contributing to open-source initiatives related to AI/ML. This hands-on experience can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss how you've turned prototypes into production-ready solutions. Be ready to share specific examples of your work that demonstrate your problem-solving skills and technical expertise.
We think you need these skills to ace Artificial Intelligence Engineer (m/f/d)
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 prototypes into production-ready solutions, especially those involving behavioural data or biometrics.
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 they relate to the role.
Showcase Your Projects: If you have any personal or professional projects that demonstrate your ability to work with complex behavioural data or MLOps pipelines, include them in your application. This can set you apart from other candidates.
Highlight Soft Skills: Don’t forget to mention your soft skills, such as collaboration and communication. The role involves working with cross-functional teams, so showcasing your ability to align tech with user-centric design is crucial.
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, to demonstrate your hands-on expertise.
✨Understand the Company’s Vision
Research the start-up's focus on behavioural biometrics and how they leverage AI. Be ready to discuss how your skills can contribute to their mission of creating unique user profiles for security, showing that you align with their goals.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your understanding of algorithms, data structures, and MLOps workflows. Practice explaining your thought process clearly, as this will showcase your analytical skills and ability to tackle complex problems.
✨Demonstrate Your Entrepreneurial Mindset
Highlight instances where you've taken initiative or worked autonomously on projects. Share your passion for human-centred AI and how you can bring innovative ideas to the table, which is crucial for a start-up environment.
