At a Glance
- Tasks: Design and deploy advanced deep learning models for global energy markets.
- Company: Nanook, a leading energy-focused investment firm with a collaborative team.
- Benefits: Competitive salary, bonuses, healthcare, gym membership, and generous pension contributions.
- Other info: Join a dynamic team solving complex problems in a supportive environment.
- Why this job: Make a real impact on energy trading decisions using cutting-edge technology.
- Qualifications: Advanced degree in a quantitative field and 4+ years of deep learning experience.
The predicted salary is between 70000 - 90000 £ per year.
Founded in 2008, Nanook is an energy-focused investment firm built by experienced energy professionals. Since launching our first fund in 2014, we have applied deep fundamental modelling of energy supply and demand to some of the most complex energy markets in the world. Today, Nanook is a specialist team solving highly complex, real-world problems in energy trading, building cutting-edge quantitative and technical solutions where rigorous analysis and disciplined thinking are critical to success.
We are looking for a Deep Learning Engineer to help design, develop, and deploy advanced deep learning models at Nanook. You will 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. The ideal candidate combines 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.
Responsibilities
Essential Skills and Experience
- Advanced degree in a quantitative field.
- 4+ years of hands-on experience building and shipping deep learning models in production, including ownership of end-to-end pipelines.
- Strong proficiency with Python and modern DL frameworks (preferably PyTorch; familiarity with JAX or TensorFlow a plus).
- Solid understanding of statistics and ML fundamentals.
- Experience of supervised learning and regression problems.
- Proficiency with GPUs and efficient training/inference for out-of-memory datasets.
- Strong data engineering fluency: experience working with large, messy datasets; familiarity with distributed compute.
- Ability to communicate clearly with both technical and commercial stakeholders.
- Ownership mindset with a track record of delivering measurable impact under time constraints.
- Ability to recognise when simpler approaches are more appropriate.
Desirable Skills and Experience
- Experience producing probabilistic and distributional forecasts.
- Experience with any of the following:
- Attention mechanisms and transformer based architectures.
- Physics informed neural networks.
- Bayesian neural networks.
- Spatiotemporal and/or graph-based modelling.
- Generative models.
- Reinforcement learning.
- Time series forecasting.
- Familiarity with reinforcement learning or generative models would be valuable, although not the focus of the role.
- Experience working with weather data, satellite imagery or spatial data.
- Domain experience in energy, commodities, or macro forecasting.
Benefits
- Competitive salary with bonus opportunities.
- Life insurance of 4x salary.
- Healthcare.
- 8% Pension contribution.
- Gym Membership.
- Cycle to work scheme.
- Employee assistance program.
- Work socials & trips.
- Amazing team & working environment.
Deep Learning Engineer in London employer: Nanook Advisors
At Nanook, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among our talented team. As a Deep Learning Engineer, you will not only tackle complex challenges in the energy sector but also benefit from competitive salaries, generous pension contributions, and a supportive environment that prioritises employee growth through continuous learning and development opportunities. Join us in a vibrant location where your contributions will directly influence trading decisions and drive impactful solutions in the global energy market.
StudySmarter Expert Advice🤫
We think this is how you could land Deep Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the energy and deep learning sectors on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your deep learning projects. Whether it’s GitHub repos or a personal website, make sure potential employers can see your work in action. This is your chance to shine and demonstrate your expertise!
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past projects in detail. Practice common deep learning interview questions and think about how you can relate your experience to the challenges at Nanook.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. Make sure your application stands out by tailoring it to the role and highlighting your relevant experience. Let’s get you on board to tackle those complex energy problems together!
We think you need these skills to ace Deep Learning Engineer in 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 deep learning models, Python, and any relevant frameworks like PyTorch. We want to see how your skills match what we're looking for!
Showcase Your Projects:Include specific projects where you've built and deployed deep learning models. Describe the challenges you faced and how you overcame them. This helps us understand your hands-on experience and problem-solving skills.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use straightforward language to explain your technical expertise and how it relates to the energy sector. We appreciate clarity as much as complexity!
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Nanook Advisors
✨Know Your Deep Learning Stuff
Make sure you brush up on your deep learning knowledge, especially around neural networks and the frameworks mentioned in the job description. Be ready to discuss your past projects in detail, focusing on how you built and deployed models from scratch.
✨Show Off Your Problem-Solving Skills
Prepare to tackle some hypothetical scenarios related to energy trading or data challenges. Think about how you would approach complex problems and be ready to explain your thought process clearly. This will show them you can think critically under pressure.
✨Communicate Like a Pro
Since you'll need to interact with both technical and commercial stakeholders, practice explaining your work in simple terms. Use examples from your experience to demonstrate how you've effectively communicated complex ideas in the past.
✨Demonstrate Ownership and Impact
Be prepared to share specific examples of how you've taken ownership of projects and delivered measurable results. Highlight any instances where you recognised when a simpler solution was more effective, as this aligns with their desire for an ownership mindset.
