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- Tasks: Join a dynamic team as a Machine Learning Engineer, focusing on innovative ML projects.
- Company: Be part of a cutting-edge tech business that's rapidly growing in the UK.
- Benefits: Enjoy a competitive salary up to £80,000 and flexible remote work options.
- Why this job: Work with advanced NLP tools and contribute to impactful technology solutions.
- Qualifications: Proficient in Python, with knowledge of AWS or GCP; experience with ML tools is a plus.
- Other info: This role is primarily remote, with occasional office visits in Milton Keynes.
The predicted salary is between 48000 - 72000 £ per year.
We are helping an innovative tech business scale their technology team in the UK. Due to continued growth and demand for their products, they now urgently need a Machine Learning Engineer to help bolster their team. This role would suit a Machine Learning Engineer who is already confident working in ML environments, especially with NLP tools. This role is remote within the UK. Their office is based in Milton Keynes - you may need to visit the office on rare occasions.
To be a successful candidate, the ideal Machine Learning Engineer will have:
- Highly skilled in Python.
- Knowledge of AWS or GCP.
- Ideally experience of SKLearn / Docker / MLFlow or PyTest.
- Excellent communication and problem-solving skills.
As a talented Machine Learning Engineer, you can expect:
- Great salary - Up to £80,000 base and package (negotiable for the right person).
If you are an ambitious Machine Learning Engineer, hit apply and we will do the rest. Please apply with your CV and we will be in touch for a confidential chat.
Machine Learning Engineer employer: Noa Recruitment
Contact Detail:
Noa Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning, especially in natural language processing (NLP). Being able to discuss recent advancements or projects you've worked on in this area can really set you apart during interviews.
✨Tip Number 2
Make sure you have hands-on experience with Python and relevant libraries like SKLearn. Consider working on personal projects or contributing to open-source projects that showcase your skills in these areas.
✨Tip Number 3
Brush up on your knowledge of cloud platforms like AWS or GCP. Being able to demonstrate your understanding of deploying machine learning models in a cloud environment can be a significant advantage.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving questions related to machine learning. Use platforms like LeetCode or HackerRank to sharpen your skills and get comfortable with coding challenges.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, AWS or GCP, and any relevant tools like SKLearn, Docker, or MLFlow. Use specific examples to demonstrate your skills in machine learning and natural language processing.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for machine learning and your problem-solving abilities. Mention why you are interested in this particular role and how your background aligns with the company's needs.
Highlight Communication Skills: Since excellent communication is key for this role, include examples in your application that demonstrate your ability to convey complex technical concepts clearly and effectively, whether in written or verbal form.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism.
How to prepare for a job interview at Noa Recruitment
✨Showcase Your Python Skills
As a Machine Learning Engineer, your proficiency in Python is crucial. Be prepared to discuss specific projects where you've used Python effectively, and consider bringing along code samples or discussing challenges you overcame using Python.
✨Familiarise Yourself with Cloud Platforms
Since the role requires knowledge of AWS or GCP, make sure you understand the basics of these platforms. Be ready to explain how you've used them in past projects, particularly in relation to machine learning applications.
✨Discuss Your Experience with ML Tools
If you have experience with SKLearn, Docker, MLFlow, or PyTest, be sure to highlight this during your interview. Prepare examples of how you've implemented these tools in your work, as this will demonstrate your hands-on experience.
✨Emphasise Communication and Problem-Solving Skills
Excellent communication and problem-solving skills are essential for this role. Think of examples where you've successfully communicated complex ideas or solved challenging problems, and be ready to share these stories during your interview.
