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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 MLOps workflows.
- Other info: Opportunity to join during seed growth for early equity consideration.
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.
Monitoring Engineer employer: 55 Exec Search
Contact Detail:
55 Exec Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Monitoring 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 about the latest trends in the industry.
✨Tip Number 2
Showcase your practical experience by working on personal projects or contributing to open-source initiatives related to AI and machine learning. This not only enhances your skills but also demonstrates your passion and commitment to potential employers.
✨Tip Number 3
Familiarise yourself with the specific technologies mentioned in the job description, such as Docker, Kubernetes, and cloud platforms like AWS or GCP. Having hands-on experience with these tools can set you apart from other candidates.
✨Tip Number 4
Prepare for interviews by practising common technical questions related to AI/ML engineering and MLOps workflows. Being able to articulate your thought process and problem-solving approach will impress interviewers and demonstrate your expertise.
We think you need these skills to ace Monitoring Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI/ML engineering, particularly focusing on your work with behavioural data and machine learning models. Use keywords from the job description to ensure your application stands out.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and machine learning. Discuss specific projects where you've transformed complex data into actionable insights, and explain how your skills align with the company's mission.
Showcase Technical Skills: In your application, emphasise your proficiency in Python and any frameworks like PyTorch or TensorFlow. Mention your experience with deploying models using Docker or Kubernetes, as these are crucial for the role.
Highlight Collaborative Experience: Since the role involves working with cross-functional teams, include examples of past collaborations. Describe how you’ve worked with others to align technology with user-centric design, showcasing your ability to communicate effectively.
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 Your Problem-Solving Ability
Expect questions that assess your ability to analyse complex behavioural data. Prepare to explain how you've turned prototypes into production-ready solutions and the impact they had.
✨Understand the Company’s Vision
Research the start-up's focus on behavioural biometrics and AI. Be ready to discuss how your skills align with their mission and how you can contribute to their growth during this exciting phase.
✨Prepare for Collaborative Scenarios
Since the role involves working with cross-functional teams, think of examples where you've successfully collaborated with others. Highlight your communication skills and how you ensure tech aligns with user-centric design.
