At a Glance
- Tasks: Build and productionise ML pipelines, optimising model performance in a fast-paced environment.
- Company: Join a major asset management firm driving data-driven initiatives.
- Benefits: Competitive contract with potential for extension and dynamic work culture.
- Other info: Ideal for engineers passionate about the full ML lifecycle and robust systems.
- Why this job: Make a real impact by deploying cutting-edge machine learning models in production.
- Qualifications: Strong Python skills, experience with Databricks and GCP, and MLOps knowledge.
The predicted salary is between 60000 - 80000 € per year.
Location: London
DW Search are partnering on a high-impact contract opportunity within a fast-paced, data-driven environment supporting portfolio company initiatives for a major asset management firm. This role sits at the intersection of Data Engineering and Machine Learning Engineering, with a strong focus on building and productionising end-to-end ML pipelines. You will be working on real-world applications of neural networks, enabling scalable feature engineering, model training, and inference in production.
Key Responsibilities
- Build and productionise feature engineering pipelines for ML models
- Develop and manage training and inference workflows at scale
- Deploy and monitor machine learning models in production environments
- Collaborate with data scientists and engineering teams to optimise model performance and reliability
- Contribute to best practices across MLOps and pipeline orchestration
Required Experience
- Strong Python fluency
- Strong hands‑on experience with Databricks
- Proven experience building production-grade data and ML pipelines
- Solid understanding of MLOps principles
- Experience working with machine learning models
- Experience with GCP
- Background in both Data Engineering and Machine Learning Engineering environments
- Exposure to scalable, high-performance data platforms
This is a strong fit for engineers who operate across the full ML lifecycle and enjoy taking models from development into robust, production systems. This is an initial 6 month contract with high likelihood of extension, apply now to be considered.
Senior Data/ML Engineer - Python/Databricks/GCP employer: DW Search
Join a leading asset management firm in London, where innovation meets opportunity. As a Senior Data/ML Engineer, you'll thrive in a dynamic work culture that prioritises collaboration and professional growth, offering you the chance to work on cutting-edge machine learning projects. With a focus on employee development and a commitment to best practices in MLOps, this role provides a unique platform for impactful contributions in a fast-paced, data-driven environment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data/ML Engineer - Python/Databricks/GCP
✨Tip Number 1
Network like a pro! Reach out to your connections in the data and ML space. Attend meetups or webinars, and don’t be shy about asking for introductions. You never know who might have the inside scoop on job openings.
✨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 and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on MLOps principles and real-world applications of neural networks. Practice explaining your past projects and how you’ve tackled challenges in building production-grade ML pipelines.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Senior Data/ML Engineer - Python/Databricks/GCP
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, Databricks, and GCP. We want to see how your skills align with the role, so don’t be shy about showcasing your relevant projects and achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and machine learning. We love seeing enthusiasm, so let us know what excites you about this opportunity.
Showcase Your Projects:If you've worked on any end-to-end ML pipelines or feature engineering projects, make sure to mention them. We’re keen to see real-world applications of your skills, so include links or descriptions of your work!
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 this exciting opportunity. Don’t miss out!
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 building and productionising ML pipelines, as this will be a key focus during the interview. Be ready to discuss specific projects where you've applied these technologies.
✨Showcase Your Problem-Solving Skills
Prepare to talk about real-world applications of neural networks you've worked on. Think of examples where you’ve tackled challenges in feature engineering or model training. This will demonstrate your hands-on experience and ability to think critically under pressure.
✨Understand MLOps Principles
Since MLOps is crucial for this role, make sure you can explain how you’ve implemented best practices in your previous work. Discuss your experience with deploying and monitoring models in production environments, as well as any tools you’ve used to optimise performance.
✨Collaborate and Communicate
Highlight your experience working with data scientists and engineering teams. Be prepared to discuss how you’ve collaborated to enhance model reliability and performance. Good communication skills are essential, so practice articulating your thoughts clearly and confidently.
