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- Tasks: Design, train, and deploy predictive models to enhance user engagement.
- Company: Leading social media platform in the UK with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Make a real impact on user experience through advanced machine learning techniques.
- Qualifications: 6-8 years of ML engineering experience and strong Python skills.
- Other info: Join a dynamic team dedicated to pushing the boundaries of technology.
The predicted salary is between 48000 - 72000 £ per year.
A leading social media platform in the United Kingdom is looking for a Senior Machine Learning Engineer to manage a project involving the development and deployment of predictive models. The successful candidate will have 6-8 years of experience in Machine Learning Engineering, expertise in Python, and a strong understanding of MLOps principles.
Responsibilities include:
- Data preprocessing
- Model development
- Monitoring
This position offers a chance to significantly enhance user engagement through data insights.
Senior ML Engineer: Design, Train & Deploy Models employer: Featmate
Contact Detail:
Featmate Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer: Design, Train & Deploy Models
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work at social media platforms. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best machine learning projects. Include links to GitHub repos or any live demos. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and MLOps knowledge. Practice coding challenges and be ready to discuss your past projects in detail. We all know that confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior ML Engineer: Design, Train & Deploy Models
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Machine Learning Engineering, especially with Python and MLOps. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about predictive models and how you can enhance user engagement. Let us know what excites you about this opportunity at our social media platform.
Showcase Your Projects: If you've worked on any cool ML projects, make sure to mention them! We love seeing practical examples of your work, especially those that involve data preprocessing and model deployment. It gives us a better idea of your hands-on experience.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Featmate
✨Know Your Models Inside Out
Make sure you can discuss the models you've developed in detail. Be ready to explain your approach to data preprocessing, model selection, and deployment strategies. This shows your depth of knowledge and experience in Machine Learning Engineering.
✨Showcase Your Python Skills
Since expertise in Python is crucial for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so brush up on your Python syntax and libraries commonly used in ML, like NumPy and Pandas.
✨Understand MLOps Principles
Familiarise yourself with MLOps best practices. Be prepared to discuss how you’ve implemented monitoring and maintenance of models in production. This will highlight your ability to manage the lifecycle of machine learning projects effectively.
✨Engage with Data Insights
Since the role focuses on enhancing user engagement through data insights, think of examples where your work has led to significant improvements. Be ready to share these stories, as they will demonstrate your impact and understanding of the business side of ML.
