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- Tasks: Develop cutting-edge ML systems for sports betting analytics and optimise performance.
- Company: Leading tech company in Greater London with a focus on innovation.
- Benefits: Hybrid working model, flexible hours, and competitive salary.
- Why this job: Join a dynamic team and make an impact in the exciting world of sports betting.
- Qualifications: Technical degree and significant software engineering experience required.
- Other info: Collaborate with quantitative researchers in a fast-paced environment.
The predicted salary is between 48000 - 72000 £ per year.
A leading technology company in Greater London seeks a Machine Learning Engineer to develop systems for sports betting analytics. You will collaborate closely with quantitative researchers, using a Python-based ML stack and optimizing performance.
Essential qualifications include a technical degree and significant software engineering experience. The role supports a hybrid working model with flexible hours, encouraging a systematic and analytical approach to design and solutions.
Senior ML Engineer - Production Trading Models, Low Latency in London employer: Longshot Systems
Contact Detail:
Longshot Systems Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer - Production Trading Models, Low Latency in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in sports betting or machine learning. A friendly chat can open doors and give you insights that might just land you that interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML and trading models. This is your chance to demonstrate your technical prowess and analytical mindset, so make it shine!
✨Tip Number 3
Prepare for the tech interview! Brush up on your Python skills and be ready to discuss your past experiences with low latency systems. We all know that confidence is key, so practice makes perfect!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior ML Engineer - Production Trading Models, Low Latency in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and any relevant machine learning projects. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about sports betting analytics and how your background makes you a perfect fit for our team. Keep it engaging and personal.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex problems in previous roles. We love candidates who can think analytically and come up with innovative solutions, especially in a fast-paced environment.
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’s super easy!
How to prepare for a job interview at Longshot Systems
✨Know Your ML Basics
Brush up on your machine learning fundamentals, especially those relevant to production trading models. Be ready to discuss algorithms, model evaluation metrics, and how you’ve applied them in past projects.
✨Showcase Your Python Skills
Since the role involves a Python-based ML stack, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice writing clean, efficient code that optimises performance.
✨Collaborate Like a Pro
This position requires close collaboration with quantitative researchers. Be prepared to share examples of how you've successfully worked in teams, tackled challenges, and communicated complex ideas clearly.
✨Embrace the Hybrid Model
Understand the benefits of hybrid working and be ready to discuss how you manage your time and productivity in such an environment. Highlight any experience you have with remote collaboration tools and flexible working arrangements.
