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- Tasks: Build and scale machine learning models for an AI-driven platform.
- Company: Leading tech company with a hybrid work culture in London.
- Benefits: Exciting projects, competitive salary, and opportunities for professional growth.
- Why this job: Join a dynamic team and work on cutting-edge machine learning systems.
- Qualifications: 5+ years in Data Engineering or Machine Learning, strong Python skills, Databricks and AWS expertise.
- Other info: Great opportunity for career advancement in a fast-paced environment.
The predicted salary is between 43200 - 72000 £ per year.
A leading technology company is seeking an experienced Machine Learning Engineer to join their hybrid team in London. This role involves building the technical foundation for an AI-driven platform, focusing on productionizing and scaling machine learning models.
Candidates should have:
- Over 5 years of experience in Data Engineering or Machine Learning
- Strong Python skills
- Expertise with Databricks and AWS services
The position offers an exciting opportunity to work on advanced machine learning systems.
ML Engineer - Production Pipelines & MLOps (Databricks/AWS) employer: Explore Group
Contact Detail:
Explore Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer - Production Pipelines & MLOps (Databricks/AWS)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that ML Engineer gig.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Databricks and AWS. We want to see your work in action, so make sure it’s easy to access and understand.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and machine learning concepts. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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 ML Engineer - Production Pipelines & MLOps (Databricks/AWS)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Data Engineering and Machine Learning. We want to see how your skills with Python, Databricks, and AWS shine through, so don’t hold back!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for this role. Share specific examples of your past work with production pipelines and scaling models to grab our attention.
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! We love seeing real-world applications of your skills, especially those that demonstrate your expertise in machine learning systems.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Explore Group
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Databricks and AWS. Brush up on your Python skills too, as you’ll likely be asked to demonstrate your coding abilities during the interview.
✨Showcase Your Experience
Prepare specific examples from your past work that highlight your experience in Data Engineering and Machine Learning. Be ready to discuss how you've productionised and scaled models, as this is a key focus for the role.
✨Understand the Company’s Vision
Research the company’s AI-driven platform and its goals. Understanding their mission will help you align your answers with what they’re looking for and show that you’re genuinely interested in contributing to their success.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, project timelines, and the challenges they face in scaling machine learning models. This not only shows your interest but also helps you gauge if the company is the right fit for you.