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- Tasks: Design low-latency trading systems and scale data pipelines for massive market data.
- Company: Join a cutting-edge tech firm revolutionising global financial markets with ML.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make an impact by optimising ML models and building high-performance systems.
- Qualifications: Strong skills in systems programming and experience with distributed systems.
- Other info: Dynamic environment with exciting challenges and career advancement opportunities.
The predicted salary is between 48000 - 72000 £ per year.
These organizations operate at the absolute bleeding edge of technology, treating the global financial markets as a complex data science problem. They are deploying massive compute clusters and proprietary machine learning models to trade billions of dollars daily.
- Architect Low-Latency Infrastructure: Design and implement the critical path for trading execution, building order management systems and market connectivity layers where performance is measured in microseconds.
- Scale Data Pipelines: Engineer elegant, distributed systems capable of ingesting and processing petabytes of market and alternative data, ensuring absolute consistency for research teams.
- Operationalize Machine Learning: Bridge the gap between research and production by deploying complex ML models into live environments under strict latency constraints.
- Optimize the Stack: Go "close to the metal" to optimize performance across networking, I/O, and compute layers, squeezing maximum efficiency out of hardware.
- Polyglot Mastery: Exceptional command of at least one major systems language (C++, Rust, Java) for low-latency components, or Python for data and ML workflows.
- Distributed Systems Expertise: Deep experience building high-throughput, fault-tolerant systems using modern messaging standards.
- Systems-Level Intuition: You are comfortable debugging and profiling at the OS level, understanding memory management, CPU architecture, and network stack optimization.
- Data Infrastructure: Familiarity with the modern data stack, including time-series databases, object stores, and streaming frameworks like Apache Flink or Spark Streaming.
- Bonus - ML Engineering: Experience with model serving, feature stores, or integrating ML pipelines into live production systems is highly valued.
Senior Software Engineer (ML) in England employer: Dex
Contact Detail:
Dex Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Software Engineer (ML) in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML and low-latency systems. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for technical interviews by practicing coding challenges and system design problems. Use platforms like LeetCode or HackerRank to sharpen your skills and get comfortable with the types of questions you might face.
✨Tip Number 4
Don’t forget to apply through our website! We’re here to help manage your applications and connect you with roles that match your skills and interests. Let’s find you that dream job together!
We think you need these skills to ace Senior Software Engineer (ML) in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Software Engineer (ML) role. Highlight your experience with low-latency infrastructure, data pipelines, and machine learning. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your background makes you a perfect fit. We love seeing enthusiasm and a clear connection to our mission.
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's optimising a data pipeline or deploying ML models, we want to see your hands-on experience and problem-solving skills!
Apply Through Our Website: Don't forget to apply through our website! It’s the easiest way for us to manage your application and connect you with Dex. Plus, we can help you find other roles that might be a great fit for you!
How to prepare for a job interview at Dex
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description. Brush up on your knowledge of C++, Rust, Java, and Python, as well as distributed systems and machine learning concepts. Being able to discuss your experience with these languages and systems confidently will impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, especially those related to low-latency infrastructure or data pipelines. Use the STAR method (Situation, Task, Action, Result) to structure your answers, demonstrating how you tackled complex problems and what the outcomes were.
✨Understand the Company’s Mission
Research the company’s approach to trading and technology. Familiarise yourself with their use of machine learning and data science in financial markets. This will not only help you answer questions more effectively but also show your genuine interest in their work and how you can contribute.
✨Prepare Questions That Matter
Think of insightful questions to ask at the end of the interview. Inquire about their current projects, team dynamics, or how they measure success in the role. This shows that you’re engaged and serious about the position, plus it gives you a better understanding of what to expect.
