Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy machine learning models that power our innovative products.
- Company: Exciting early-stage startup on a mission to revolutionise technology.
- Benefits: Competitive salary, dynamic work environment, and opportunities for growth.
- Why this job: Make a real impact by turning ideas into features customers love.
- Qualifications: 2+ years in ML or data roles, strong Python skills, and a passion for learning.
- Other info: Join a collaborative team and help shape our technical culture.
The predicted salary is between 60000 - 84000 ÂŁ per year.
As a Machine Learning Engineer (NLP), you will work with our small but growing team and play an active role in building our Machine Learning/NLP capability. You will be responsible for developing and refining the NLP algorithms and infrastructure of our AI-powered design platform. You will apply SOTA NLP techniques to solve complex problems while collaborating with cross-functional teams.
As Machine Learning Engineer (NLP), you will be responsible for:
Building and deploying NLP models using the latest techniques to solve real business problems at scale, and exposing them through APIs
Working with unstructured data to extract insights and build robust data pipelines
Evaluating, tracking, and improving the performance of NLP models through MLOps
Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution
Communicating technical concepts and results to non-technical stakeholders
Playing an active role in the wider team and growth of the business
To be successful in this role you will have:
Building and deploying NLP models using the latest techniques to solve real business problems at scale, and exposing them through APIs
Working with unstructured data to extract insights and build robust data pipelines
valuating, tracking, and improving the performance of NLP models through MLOps
Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution
Communicating technical concepts and results to non-technical stakeholders
Playing an active role in the wider team and growth of the business, and building scalable systems
Have experience working with Azure, AWS or GCP
Be a relentless problem solver, understanding requirements and designing solutions
An entrepreneurial spirit and an interest in building world-changing ethical AI solutions
Excellent communication skills and be able to explain complex technical concepts to non-technical stakeholders
Be detail-oriented and able to manage multiple projects simultaneously
Start-up life is not for everyone! To really thrive with us you will be \âStartâup ready\â. You are naturally proactive, open to change, have a continuous improvement mindset, are flexible, happy to go beyond your brief, enjoy working at pace and are comfortable with ambiguity.
And finally, you will really resonate with our values:
Customer Focus â we are obsessive about delivering value and reducing complexity for customers
Collaboration: we\âre all about the team â collaborating, supporting and recognising everyone\âs contributions
Openness & Honesty: we are open, honest, and straightâtalking with each other and our customers
Authenticity & Humility: we bring our whole selves to work, and we have the humility and selfâhonesty to admit when we are wrong
#J-18808-Ljbffr
Machine Learning Engineer employer: Mekion Consulting
Contact Detail:
Mekion Consulting Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Machine Learning Engineer
â¨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really set you apart from the crowd.
â¨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and approach real-world problems!
â¨Tip Number 4
Donât forget to apply through our website! Itâs the best way to ensure your application gets seen by the right people. Plus, it shows youâre genuinely interested in joining our team and being part of our mission.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight relevant experience, especially with Python and ML frameworks like TensorFlow or PyTorch. We want to see how your skills align with what weâre looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for machine learning and how you can contribute to our mission. We love seeing enthusiasm and a bit of personality, so donât hold back!
Showcase Your Projects: If you've worked on any cool projects, make sure to mention them! Whether it's deploying ML models or building data pipelines, we want to know about your hands-on experience. Include links to your GitHub or portfolio if you have them!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures youâre considered for the role. Plus, itâs super easy!
How to prepare for a job interview at Mekion Consulting
â¨Know Your Stuff
Make sure you brush up on your machine learning concepts and frameworks like TensorFlow and PyTorch. Be ready to discuss your past projects in detail, especially how you designed, trained, and deployed models. This shows youâre not just familiar with the theory but have practical experience too.
â¨Show Your Problem-Solving Skills
Prepare to tackle some real-world problems during the interview. Think of examples where you've solved complex issues using ML techniques. This will demonstrate your ability to think critically and apply your knowledge effectively, which is crucial for the role.
â¨Communicate Clearly
Youâll need to explain complex concepts to both technical and non-technical folks. Practice articulating your thoughts clearly and concisely. Use analogies or simple terms when necessary to ensure everyone understands your ideas.
â¨Be Ready to Collaborate
Since this role involves working closely with product and engineering teams, be prepared to discuss how youâve collaborated in the past. Share examples of how youâve integrated ML into customer-facing features and how you handle feedback from team members.