At a Glance
- Tasks: Design and deploy advanced deep learning models for global energy market challenges.
- Company: Join a specialist Hedge Fund with a focus on innovation and collaboration.
- Benefits: Earn up to £150k, enjoy bonuses, private medical insurance, and company retreats.
- Other info: Work in a supportive team environment with excellent career development opportunities.
- Why this job: Make a real impact on trading decisions using cutting-edge technology.
- Qualifications: Strong Python skills and experience with deep learning tools like TensorFlow.
The predicted salary is between 108000 - 180000 £ 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.
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
Your role:
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'll 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’ll 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’re collaborative with great communication skills
Apply now to find out more about this Deep Learning Engineer (Python TensorFlow Lattice TFL) opportunity.
At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We’re an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.
Deep Learning Engineer Python TensorFlow employer: Client Server
Join a leading Hedge Fund in North London as a Deep Learning Engineer, where you'll be part of a dynamic and collaborative team dedicated to tackling complex challenges in the global energy market. With a competitive salary of up to £150k plus bonuses, generous benefits including an 8% non-contributory pension, private medical insurance, and unique company retreats, this role offers not just a job but a pathway for professional growth and development in a supportive environment that values diversity and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Deep Learning Engineer Python TensorFlow
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, conferences, or even online webinars. The more you engage with others, the better your chances of landing that Deep Learning Engineer role.
✨Show Off Your Skills
Create a portfolio showcasing your deep learning projects. Whether it's GitHub repos or a personal website, let your work speak for itself. Potential employers love to see what you've done with Python and TensorFlow!
✨Ace the Interview
Prepare for technical interviews by brushing up on your deep learning concepts and coding skills. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key!
✨Apply Through Us
Don't forget to apply through our website! We’re here to help you find the right fit for your skills and aspirations. Plus, we know the ins and outs of the companies looking for talent like yours.
We think you need these skills to ace Deep Learning Engineer Python TensorFlow
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with deep learning and Python. We want to see how your skills align with the role, so don’t be shy about showcasing your 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 deep learning and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills:Don’t forget to mention your hands-on experience with tools like TensorFlow Lattice and any other relevant technologies. We’re looking for someone who can hit the ground running, so let us know what you’ve worked on!
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 don’t miss out on any important updates from 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 and other tools mentioned in the job description. Be ready to discuss your hands-on experience with building and shipping models, as well as any specific projects you've worked on that relate to energy markets.
✨Showcase Your Problem-Solving Skills
Prepare to talk about complex problems you've tackled in previous roles. Think of examples where you designed and deployed models from scratch, and how those models made a real impact. This will demonstrate your ability to handle the challenges they'll throw your way.
✨Communicate Clearly and Collaboratively
Since you'll be working in a team environment, practice explaining your technical work in simple terms. They’ll want to see that you can communicate effectively with both technical and non-technical team members, so be ready to showcase your collaborative spirit.
✨Understand the Business Context
Familiarise yourself with the energy market and how deep learning can influence trading decisions. Showing that you understand the business side of things will set you apart and demonstrate that you're not just a tech whiz, but also someone who can contribute to strategic discussions.
