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- Tasks: Lead a talented team to develop cutting-edge machine learning infrastructure.
- Company: Top quantitative fund in London with a focus on innovation.
- Benefits: Short interview process and significant responsibilities await you.
- Why this job: Make an impact in the exciting world of machine learning and distributed systems.
- Qualifications: 8+ years in software engineering, expertise in distributed systems, and strong Python skills.
- Other info: Join a high-performing team and elevate your career in a dynamic environment.
The predicted salary is between 43200 - 72000 £ per year.
A top quantitative fund in London is seeking an experienced Engineering Manager/Tech Lead to lead a high-performing team focused on machine learning infrastructure. In this hands-on leadership role, you will direct the development of advanced ML capabilities and manage a team of 6–7 engineers.
The ideal candidate has over 8 years in software engineering with expertise in distributed systems and strong skills in Python. This position offers a short interview process and significant responsibilities.
Engineering Manager, ML Infra & Distributed Systems employer: Oxford Knight
Contact Detail:
Oxford Knight Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Engineering Manager, ML Infra & Distributed Systems
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work at top quantitative funds. A personal referral can make all the difference in getting your foot in the door.
✨Tip Number 2
Prepare for technical interviews by brushing up on your Python skills and understanding distributed systems inside out. We recommend doing mock interviews with friends or using online platforms to simulate the real deal.
✨Tip Number 3
Showcase your leadership experience! Be ready to discuss how you've managed teams and projects in the past. Highlight specific examples where you directed development efforts and achieved significant results.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Engineering Manager, ML Infra & Distributed Systems
Some tips for your application 🫡
Show Off Your Experience: When you’re writing your application, make sure to highlight your experience in software engineering and distributed systems. We want to see how your background aligns with the role, so don’t hold back on those impressive projects you've led!
Be Specific About Your Skills: Mention your expertise in Python and any relevant machine learning capabilities. We love details, so if you've worked on specific ML projects or technologies, let us know! This helps us understand how you can contribute to our team.
Leadership Matters: Since this is a leadership role, share examples of how you've successfully managed teams in the past. We’re looking for someone who can inspire and guide others, so include any achievements that showcase your leadership style.
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 makes the process smoother for everyone involved!
How to prepare for a job interview at Oxford Knight
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of distributed systems and machine learning infrastructure. Be ready to discuss your experience with Python and how you've applied it in previous projects. This will show that you're not just a manager but also technically savvy.
✨Showcase Your Leadership Style
Prepare to talk about your leadership approach and how you manage teams. Think of specific examples where you've successfully led a team through challenges or implemented new processes. This will help the interviewers see how you can fit into their high-performing environment.
✨Ask Insightful Questions
Come prepared with questions that demonstrate your interest in the company’s goals and challenges. Ask about their current ML projects or how they envision the future of their infrastructure. This shows that you’re not just looking for a job, but are genuinely interested in contributing to their success.
✨Be Ready for Hands-On Scenarios
Since this is a hands-on role, expect technical questions or scenarios during the interview. Practice explaining your thought process when solving problems related to ML infrastructure or distributed systems. This will highlight your practical skills and ability to lead by example.