Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy advanced deep learning models for energy market forecasting.
- Company: Join a specialist Hedge Fund with a focus on innovation and collaboration.
- Benefits: Earn up to £150k, enjoy bonuses, private medical insurance, and career development.
- Other info: Work in a supportive team environment with opportunities for exciting company retreats.
- Why this job: Make a real impact on trading decisions using cutting-edge deep learning techniques.
- Qualifications: Strong Python skills and experience with TensorFlow Lattice and deep learning models.
The predicted salary is between 43200 - 72000 £ per year.
Do you have expertise with Deep Learning within commercial environments? You could be joining a specialist Hedge Fund and working on long term strategic projects which involve implementing quantitative statistical models that are used to forecast elements of demand and supply of energy for European markets.
As a Deep Learning Engineer you will design, develop and deploy advanced deep learning models to tackle some of the most complex problems in global energy markets, applying cutting-edge neural network and deep learning techniques across diverse and challenging data sets. You will combine deep technical expertise in neural networks and deep learning with practical experience delivering models end-to-end, from research to production, in a high-performance environment. Your work will directly impact trading decisions, turning sophisticated models into actionable insights.
Location / WFH: You will be working in a collegiate team environment based in North London with a small group of accomplished software/data engineers and finance entrepreneurs.
About you:
- You have an excellent academic record of achievement; 2.1 or above in a quantitative discipline at BSc, from a Russell Group university.
- You have strong hands-on experience building and shipping deep learning models in production, including ownership of end-to-end pipelines.
- You have strong Python skills.
- You have experience with deep learning tools such as TensorFlow Lattice (TFL), OptNet, DeepXDE.
- You have a strong understanding of statistics and Machine Learning fundamentals.
- You have experience of working with large, messy datasets.
- You are collaborative with great communication skills.
What’s in it for you:
- Up to £150k + bonus.
- Pension (8% non-contributory).
- Private Medical Insurance.
- Life Assurance.
- Training and career development opportunities.
- Employee Assistance Programme.
- Company retreats such as Winter skiing trips and Summer weekends away.
Deep Learning Engineer in City of London employer: Client Server
Contact Detail:
Client Server Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Deep Learning Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working in hedge funds or deep learning. Attend meetups or webinars, and don’t be shy about asking for informational interviews. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your deep learning projects, especially those involving TensorFlow Lattice or similar tools. Share your work on platforms like GitHub or LinkedIn to grab the attention of potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and deep learning concepts. Practice coding challenges and be ready to discuss your past projects in detail. Remember, they want to see how you think and solve problems!
✨Tip Number 4
Apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your experience with end-to-end deep learning pipelines and your collaborative spirit. Let’s get you that job!
We think you need these skills to ace Deep Learning Engineer in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Deep Learning Engineer role. Highlight your experience with TensorFlow Lattice, OptNet, and DeepXDE, and don’t forget to showcase your hands-on experience in building and shipping deep learning models.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about deep learning and how your skills can contribute to our team. Be specific about your achievements and how they relate to the role.
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's a personal project or something from your previous job, demonstrating your practical experience with large datasets and end-to-end pipelines will set you apart.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Client Server
✨Know Your Deep Learning Stuff
Make sure you brush up on your deep learning knowledge, especially around TensorFlow Lattice, OptNet, and DeepXDE. Be ready to discuss specific projects where you've built and deployed models, as well as the challenges you faced and how you overcame them.
✨Show Off Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice writing clean, efficient code that showcases your understanding of deep learning libraries and frameworks.
✨Talk About Data Handling
Be prepared to discuss your experience with large, messy datasets. Share examples of how you've cleaned, processed, and transformed data for model training. Highlight any techniques you've used to handle data quality issues, as this will show your practical experience in real-world scenarios.
✨Emphasise Collaboration and Communication
This role involves working in a team, so it's crucial to demonstrate your collaborative spirit. Prepare examples of how you've worked with others, communicated complex ideas, and contributed to team success. This will help show that you're not just a tech whiz but also a great team player.