At a Glance
- Tasks: Build and optimise machine learning pipelines for real-world applications.
- Company: Join a leading asset management firm in London.
- Benefits: Competitive contract rate and the chance to work on impactful projects.
- Other info: Exciting opportunity to enhance your career in a dynamic environment.
- Why this job: Make a difference by deploying cutting-edge ML models in production.
- Qualifications: Strong Python skills and experience with Databricks required.
The predicted salary is between 60000 - 80000 € per year.
DW Search is looking for a Data and Machine Learning Engineer in London to build and productionise feature engineering pipelines for ML models. This contract opportunity supports initiatives for a major asset management firm and involves deploying and optimizing machine learning models in production.
The ideal candidate will have strong Python fluency and hands-on experience with Databricks, among other qualifications.
Production ML Engineer - Python, Databricks & GCP in London employer: DW Search
At DW Search, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London-based team enjoys competitive benefits, including flexible working arrangements and opportunities for professional development, making it an ideal environment for those looking to advance their careers in data and machine learning. Join us to be part of impactful projects with a major asset management firm, where your contributions will be valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land Production ML Engineer - Python, Databricks & GCP in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, Databricks, and GCP. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice common interview questions and maybe even do some mock interviews with friends or mentors.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Production ML Engineer - Python, Databricks & GCP in London
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your Python fluency in your application. We want to see how you've used Python in real projects, especially in relation to machine learning and data engineering.
Talk About Your Databricks Experience:If you've worked with Databricks, let us know! Share specific examples of how you've used it to build or optimise ML pipelines. This will really help your application stand out.
Focus on Production Experience:Since this role is all about deploying and optimising models in production, be sure to mention any relevant experience you have. We love to see candidates who can demonstrate their ability to take models from development to deployment.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and we can’t wait to see what you bring to the table!
How to prepare for a job interview at DW Search
✨Know Your Tech Stack
Make sure you brush up on your Python skills and get familiar with Databricks and GCP. Be ready to discuss how you've used these technologies in past projects, as this will show your hands-on experience and technical fluency.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced while building or optimising ML models. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easier for the interviewer to see your thought process and problem-solving abilities.
✨Understand Feature Engineering
Since the role involves building feature engineering pipelines, be prepared to explain your approach to feature selection and transformation. Discuss any tools or techniques you've used to enhance model performance, as this will demonstrate your expertise in the area.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about their current ML projects or how they measure the success of deployed models. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
