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For Companies At a Glance
- Tasks: Develop and deploy cutting-edge machine learning models for trading financial securities.
- Company: Innovative startup focused on revolutionising trading with machine learning.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Dynamic startup culture with a focus on innovation and collaboration.
- Why this job: Join a visionary team aiming for 1 billion AUM in just 24 months.
- Qualifications: Proven ML experience, strong Python skills, and a PhD from a top university.
The predicted salary is between 72000 - 108000 £ per year.
We believe trading has become so complex that machines will be fundamentally better than humans. As such, Alphalupe is developing a fully systematised machine learning approach into trading any financial security. After a period of beta testing, we have now received investment and are operating a fund comprised of some of the most sophisticated wealth managers in the world. We have a vision and a clear path to achieve 1 billion AUM in the next 24 months.
The Challenge
We are going to deeply understand how the economy works, how investors deploy their capital, and how capital markets work. Furthermore, the market is full of trading algorithms, knowledgeable human traders, but also biased, occasional traders. Together they move the market and predicting their behaviour is a non-trivial task. Success is not guaranteed. But with intelligence, agility, action and perseverance, we will make big strides.
As an early stage startup, we will build the culture, processes and product so you should be ready to be flexible.
How we Work
- We move fast, but don't break things as we are responsible for our customers' assets.
- We attribute high ownership but expect high communication.
- We are frugal and believe that constraints spark innovation.
- We like sharing and helping others, but we measure ourselves by what we do and achieve.
- We prefer being in the office and all its serendipitous events that lead to innovation.
- We are honest, trustworthy, adult problem solvers but we have low egos, don't like drama nor toxic office politics.
- We are focused on our product, solve the right problems and navigate away from pitfalls.
What you will Bring
We are looking for deep expertise in several machine learning techniques and practical experience in managing the lifecycle of your models. You will be responsible for understanding the requirements, creating, testing, training your solutions and deploying them into production. We look for people that can quickly learn new fields and that have shown that before.
Requirements
- Proven experience in developing and deploying ML models in the past.
- Extensive experience using ML frameworks like PyTorch / TensorFlow.
- Product mindset and deep understanding of data and model lifecycles.
- Experience building at scale in Python / NumPy / Pandas or others.
- Experience with ETL, data management, data augmentation and data engineering.
- Orchestration tools and infrastructure knowledge (AWS or others).
- Financial industry experience.
- Experience with transformers and embeddings.
- A degree (PhD) from a global top university.
Senior Machine Learning Engineer in London employer: AlphaLupe.ai
Contact Detail:
AlphaLupe.ai Recruiting Team
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 people in the industry, attend meetups, and connect with current employees at Alphalupe. A personal introduction can make all the difference when you're trying to land that Senior Machine Learning Engineer role.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your machine learning projects and be ready to discuss them in detail. This is your chance to demonstrate your expertise in ML frameworks like PyTorch or TensorFlow and how you've tackled real-world problems.
✨Tip Number 3
Be flexible and adaptable! Since Alphalupe is an early-stage startup, they value candidates who can pivot quickly and embrace change. Highlight your ability to learn new fields and adapt to evolving challenges during interviews.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in being part of the Alphalupe team and their mission to revolutionise trading with machine learning.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Show Your Passion for Machine Learning: When writing your application, let us see your enthusiasm for machine learning! Share specific projects or experiences that highlight your skills and how they relate to our mission at Alphalupe. We want to know what drives you in this field!
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Senior Machine Learning Engineer role. Highlight relevant experience with ML frameworks like PyTorch or TensorFlow, and don’t forget to mention any financial industry experience. We love seeing how your background aligns with our needs!
Be Clear and Concise: Keep your application clear and to the point. Use straightforward language to describe your achievements and skills. We appreciate a well-structured application that makes it easy for us to see why you’re a great fit for our team!
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 the role. Plus, it shows you’re proactive and keen to join our innovative team!
How to prepare for a job interview at AlphaLupe.ai
✨Know Your ML Models Inside Out
Make sure you can discuss your past experiences with machine learning models in detail. Be ready to explain the lifecycle of your models, from development to deployment, and how you've tackled challenges along the way. This shows you have the hands-on experience they’re looking for.
✨Understand the Financial Landscape
Since this role is in the financial sector, brush up on your knowledge of how capital markets operate. Familiarise yourself with trading algorithms and investor behaviours. Being able to connect your technical skills to real-world applications in finance will set you apart.
✨Showcase Your Product Mindset
Demonstrate that you understand the importance of a product mindset. Talk about how you’ve approached problems with a focus on user needs and outcomes. Highlight any experience you have in building scalable solutions and how you’ve iterated based on feedback.
✨Be Ready for Technical Questions
Prepare for in-depth technical questions related to ML frameworks like PyTorch or TensorFlow. Brush up on your Python skills, especially with libraries like NumPy and Pandas. They might also ask about ETL processes, so be prepared to discuss your data management strategies.