At a Glance
- Tasks: Join a dynamic team to develop innovative machine learning solutions.
- Company: Innovative tech business with a focus on growth and technology.
- Benefits: Competitive salary up to £75k, remote work, and career development opportunities.
- Other info: Remote role with occasional office visits in Milton Keynes.
- Why this job: Make an impact in the exciting field of machine learning and NLP.
- Qualifications: Proficient in Python, with knowledge of AWS or GCP.
The predicted salary is between 65000 - 75000 £ 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 75,000 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
As a Product Owner at this innovative technology business, you will thrive in a supportive and adaptive culture that prioritises your professional growth. With access to structured training and career progression opportunities, you can take the lead on critical projects while enjoying a competitive salary package. The remote work flexibility, combined with monthly team interactions in Milton Keynes, creates a unique environment that fosters collaboration and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Noa Recruitment or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Noa Recruitment.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Noa Recruitment.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Noa Recruitment that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Noa Recruitment.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Noa Recruitment and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Noa Recruitment
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Noa Recruitment uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
