At a Glance
- Tasks: Build and productionise ML pipelines, deploy models, and optimise performance.
- Company: Join a leading asset management firm in a fast-paced, data-driven environment.
- Benefits: Competitive day rate, flexible contract, and potential for extension.
- Other info: Ideal for engineers passionate about the full ML lifecycle.
- Why this job: Make a real impact by working on cutting-edge ML applications.
- Qualifications: Strong Python skills, Databricks experience, and MLOps knowledge required.
Location: London
Contract: Outside IR35
Day Rate: Negotiable ~ £600-£700
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
- 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 in London employer: DW Search
Join a leading asset management firm in London as a Senior Data/ML Engineer, where you will thrive in a dynamic and innovative work culture that prioritises collaboration and professional growth. With competitive day rates and the opportunity to work on cutting-edge machine learning projects, you will be part of a team that values your expertise and encourages continuous learning in a fast-paced environment. This role not only offers the chance to make a significant impact on real-world applications but also provides a supportive atmosphere for career advancement.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data/ML Engineer - Python/Databricks/GCP in London
✨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 referrals. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, Databricks, and GCP. We recommend using GitHub to share your code and demonstrate your ability to build production-grade ML pipelines.
✨Tip Number 3
Prepare for interviews by brushing up on MLOps principles and real-world applications of neural networks. We suggest doing mock interviews with friends or using online platforms to get comfortable discussing your experience and technical skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for talented individuals who can contribute to our fast-paced, data-driven environment.
We think you need these skills to ace Senior Data/ML Engineer - Python/Databricks/GCP in London
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 relevant projects or 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 and a clear understanding of the role’s responsibilities.
Showcase Your Projects:If you've worked on any ML pipelines or data 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 Inside Out
Make sure you’re well-versed in Python, Databricks, and GCP. Brush up on your knowledge of MLOps principles and be ready to discuss how you've built and productionised ML pipelines in the past. Real-world examples will help you stand out!
✨Showcase Your Collaboration Skills
This role involves working closely with data scientists and engineering teams. Be prepared to share experiences where you’ve collaborated effectively to optimise model performance. Highlighting teamwork can really make a difference.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about feature engineering, model training, and inference workflows. Practise explaining complex concepts clearly and concisely, as this will demonstrate your expertise and communication skills.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company’s projects and challenges. Inquire about their current ML initiatives or how they approach MLOps. This shows you’re genuinely engaged and thinking ahead.
