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- Tasks: Design and optimise high-performance machine learning models for real-world applications.
- Company: Leading tech organisation fostering collaboration and innovation.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Why this job: Join a forward-thinking team and make an impact with cutting-edge technology.
- Qualifications: Degree in relevant field and strong skills in Python and C/C++.
- Other info: Permanent role with excellent career advancement potential.
The predicted salary is between 30000 - 49000 £ per year.
We are working in partnership with a leading technology organisation to recruit an experienced Machine Learning Engineer. The successful candidate will design, train, and optimise high-performance machine learning models, build and manage datasets for real-world sensing systems, and clearly communicate technical work to stakeholders.
Based in North Somerset, you will be part of a collaborative and forward-thinking environment that encourages rapid prototyping and experimentation. You will work within multidisciplinary teams to develop, validate and deploy machine learning models to meet challenging customer requirements.
Key Responsibilities- Develop and train neural network models using frameworks such as PyTorch and TensorFlow
- Select and adapt model architectures to meet specific project requirements
- Build, curate, and manage training datasets, including data augmentation, feature extraction, and labelling
- Conduct model training, validation, and performance optimisation
- Collaborate with software engineers to integrate models into embedded or application environments
- Produce clear technical documentation and communicate findings to technical and non-technical audiences
- Degree in Computer Science, Engineering, Mathematics, or related field
- Strong development skills in Python and C/C++
- Experience with neural network architectures including RNNs, transformers, and vector quantisation
- In-depth knowledge of machine learning architectures and training algorithms
- Experience in model training, quantisation, and conversion for inference
- Hands-on experience with data preparation, augmentation, and feature extraction
- Excellent communication and technical writing skills
- UK national, eligible for security clearance
Due to the nature of work at our client's site, these vacancies are only open to British Citizens who hold security clearance or can obtain it.
This is a permanent role with a salary range of £38,000-£70,000.
Electus Recruitment Solutions provides specialist engineering and technical recruitment solutions to a number of high technology industries. We thank you for your interest in this vacancy. If you do not hear from us within seven working days, please presume your application has been unsuccessful on this occasion. You are free to resubmit your CV or details in the future, and we shall assess your suitability then.
Machine Learning Engineer employer: Electus Recruitment Solutions
Contact Detail:
Electus Recruitment Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Machine Learning Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving PyTorch and TensorFlow. We recommend sharing your work on GitHub or even writing a blog post about your experiences – it’s a great way to catch the eye of potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. We suggest doing mock interviews with friends or using online platforms. Being able to clearly communicate your technical work is key, so practice explaining your projects to non-technical folks too!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented Machine Learning Engineers like you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with neural networks, Python, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific examples of machine learning models you've developed or optimised. If you've used frameworks like PyTorch or TensorFlow, let us know! This helps us understand your hands-on experience and problem-solving skills.
Communicate Clearly: Since you'll need to communicate technical work to various stakeholders, make sure your application reflects your ability to explain complex concepts simply. Use clear language and avoid jargon where possible – we appreciate straightforward communication!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at Electus Recruitment Solutions
✨Know Your Models Inside Out
Make sure you’re well-versed in the neural network architectures mentioned in the job description, like RNNs and transformers. Be ready to discuss your experience with these models and how you've applied them in real-world scenarios.
✨Showcase Your Data Skills
Prepare to talk about your experience with data preparation, augmentation, and feature extraction. Bring examples of datasets you've built or managed, and be ready to explain your approach to curating high-quality training data.
✨Communicate Clearly
Since you'll need to communicate technical work to both technical and non-technical audiences, practice explaining complex concepts in simple terms. Think of a few examples where you successfully conveyed your findings to stakeholders.
✨Collaborate and Integrate
Highlight any past experiences working with software engineers to integrate machine learning models into applications. Discuss how you approached collaboration and what tools or methods you used to ensure smooth integration.
