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, flexible working, and valuable industry experience.
- Other info: Exciting opportunity to work on high-profile projects in the finance sector.
- Why this job: Make an impact by deploying cutting-edge ML models in a dynamic environment.
- Qualifications: Strong Python skills and hands-on 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 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 grow their careers in data and machine learning within the asset management sector.
StudySmarter Expert Advice🤫
We think this is how you could land Production ML Engineer - Python, Databricks & GCP
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working with ML and Python. A friendly chat can lead to opportunities you might not find on job boards.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with Databricks and GCP. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and ML concepts. We recommend doing mock interviews or coding challenges 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 by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Production ML Engineer - Python, Databricks & GCP
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 how you've tackled challenges in a production environment.
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’re well-versed in Python, Databricks, and GCP. Brush up on your knowledge of these technologies and be ready to discuss how you've used them in past projects. Having specific examples will show that you can hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to talk about challenges you've faced while building or optimising ML models. Think of a couple of scenarios where you had to troubleshoot or innovate. This will demonstrate your ability to think critically and adapt in a fast-paced environment.
✨Understand Feature Engineering
Since the role involves feature engineering pipelines, make sure you can explain what feature engineering is and why it’s crucial for ML models. Be ready to discuss techniques you've used and how they impacted model performance.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current projects, the company culture, or their approach to deploying ML models. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
