At a Glance
- Tasks: Build and deploy cutting-edge ML pipelines in a fast-paced environment.
- Company: Join a major asset management firm with a focus on innovation.
- Benefits: Competitive contract rate, hybrid working, and potential for extension.
- Other info: Collaborative team environment with opportunities for growth.
- Why this job: Make a real impact by working on scalable ML applications.
- Qualifications: Strong Python skills and experience with ML pipelines and MLOps.
The predicted salary is between 60000 - 80000 € per year.
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 (neural networks)
- 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
- Proven experience building production-grade data and ML pipelines
- Solid understanding of MLOps principles
- Experience working with machine learning models
- Some project experience with Databricks
- Cloud experience - open to Azure/ GCP/ AWS
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, outside IR35 with high likelihood of extension. A rate guidance is provided but the focus is on the right person so open to contractors outside of this range.
Senior Machine Learning Engineer in London employer: DW Search
Join a leading asset management firm in London as a Senior Machine Learning Engineer, where you will thrive in a dynamic, data-driven environment that champions innovation and collaboration. With a strong emphasis on employee growth, you will have access to cutting-edge technology and the opportunity to work alongside talented professionals, all while enjoying the flexibility of hybrid working arrangements. This role not only offers competitive compensation but also the chance to make a significant impact by developing and optimising machine learning pipelines that drive real-world applications.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that Senior Machine Learning Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML pipelines and MLOps. This will give potential employers a taste of what you can do and set you apart from the competition.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python, cloud platforms, and production-grade ML pipelines. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with building and productionising ML pipelines. We want to see your Python fluency and any relevant projects you've worked on, especially with Databricks or cloud platforms like Azure, GCP, or AWS.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Talk about your experience in MLOps and how you’ve optimised model performance in past projects. We love a good story!
Showcase Your Projects:If you've got any standout projects that demonstrate your skills in ML and data engineering, make sure to include them. We’re keen to see real-world applications of your work, so don’t hold back on the details!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it makes the whole process smoother for everyone!
How to prepare for a job interview at DW Search
✨Know Your ML Pipelines
Make sure you can discuss your experience with building and productionising ML pipelines in detail. Be ready to explain the challenges you faced and how you overcame them, especially in relation to neural networks.
✨Brush Up on MLOps Principles
Since this role has a strong focus on MLOps, ensure you understand the key principles and best practices. Be prepared to share examples of how you've implemented these in past projects, particularly around model deployment and monitoring.
✨Showcase Your Collaboration Skills
Collaboration is key in this role, so think of specific instances where you've worked closely with data scientists or engineering teams. Highlight how you contributed to optimising model performance and reliability.
✨Familiarise Yourself with Cloud Platforms
Whether it's Azure, GCP, or AWS, make sure you're comfortable discussing your cloud experience. Be ready to talk about how you've leveraged cloud services for ML workflows and any relevant project experiences, especially with Databricks.
