At a Glance
- Tasks: Design and deploy cutting-edge AI/ML solutions for real-world applications.
- Company: Join a dynamic startup environment focused on innovation and growth.
- Benefits: Remote work flexibility, competitive salary, and opportunities for professional development.
- Other info: Collaborative culture with excellent career advancement opportunities.
- Why this job: Make a real impact in the AI/ML field while working with modern technologies.
- Qualifications: 5-7 years in Data Science/AI-ML with strong Python and deep learning skills.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a skilled AI/ML Engineer – Data Science to design, develop, and deploy scalable machine learning and deep learning solutions. The ideal candidate will have hands-on experience in model development, NLP, cloud platforms, and production-grade deployment, along with prior exposure to fast-paced startup environments.
Key Responsibilities
- Design, build, and optimize machine learning and deep learning models for real-world applications.
- Develop and deploy AI/ML solutions using modern Python-based frameworks.
- Implement NLP models and solutions for structured and unstructured data.
- Build and maintain production-ready ML pipelines, ensuring scalability and reliability.
- Collaborate with cross-functional teams including engineering, product, and data teams.
- Ensure proper model governance, versioning, and CI/CD practices for ML workflows.
Required Skills & Experience
- Data Science & Deep Learning: Strong hands-on experience in Deep Learning using PyTorch or TensorFlow.
- Programming & Frameworks: Proficiency in Python. Experience with web/API frameworks such as Django, Flask, or FastAPI.
- AI & NLP: Practical experience in Artificial Intelligence and Natural Language Processing (NLP).
- Cloud Platforms: Hands-on experience with AWS or Azure environments.
- MLOps & Deployment: Experience in model deployment and productionization, model governance and lifecycle management, version control tools such as Git, and CI/CD pipelines for ML workflows.
Work Environment
Prior experience working in a startup or high-growth environment is mandatory.
Eligibility Criteria
- Permanent UK Citizenship (mandatory).
- 5–7 years of relevant experience specifically in Data Science and AI/ML Engineering.
Preferred Attributes
- Strong problem-solving and analytical thinking.
- Ability to work independently in a remote or hybrid setup.
- Effective communication and collaboration skills.
AI/ML Engineer in Wolverhampton employer: Idyllic Services
Join a forward-thinking company that values innovation and creativity, offering a dynamic work culture where your contributions as an AI/ML Engineer will directly impact cutting-edge projects. With flexible remote and hybrid working options, you will enjoy a healthy work-life balance while benefiting from continuous professional development opportunities and collaboration with talented teams across the UK. Embrace the chance to grow in a fast-paced environment that champions diversity and encourages your unique ideas.
StudySmarter Expert Advice🤫
We think this is how you could land AI/ML Engineer in Wolverhampton
✨Tip Number 1
Network like a pro! Reach out to folks in the AI/ML space on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving deep learning and NLP. This will give potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by brushing up on common AI/ML questions and coding challenges. Practising with friends or using online platforms can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace AI/ML Engineer in Wolverhampton
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI/ML Engineer role. Highlight your experience in data science, deep learning, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI/ML and how your background makes you a great fit for our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects:If you've worked on any cool AI/ML projects, make sure to mention them! Whether it's a personal project or something from a previous job, we want to see your hands-on experience and creativity in action.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining the StudySmarter family!
How to prepare for a job interview at Idyllic Services
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of deep learning frameworks like PyTorch and TensorFlow. Be ready to discuss your hands-on experience with these tools, as well as any projects you've worked on that showcase your skills in AI/ML.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex problems in previous roles. Highlight your analytical thinking and how you've applied it to develop scalable machine learning solutions or optimise existing models.
✨Familiarise Yourself with CI/CD Practices
Since model governance and lifecycle management are key aspects of the role, be prepared to discuss your experience with CI/CD pipelines for ML workflows. Bring examples of how you've implemented version control and ensured reliability in your deployments.
✨Communicate Effectively
As collaboration is crucial in this role, practice articulating your thoughts clearly. Be ready to explain technical concepts in a way that non-technical team members can understand, showcasing your ability to work well in cross-functional teams.
