At a Glance
- Tasks: Build systems and pipelines for data-driven decision-making across teams.
- Company: Join a high-impact tech team at Perplexity, shaping the future of AI.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Work in a dynamic environment with a focus on innovation and collaboration.
- Why this job: Make a real impact by improving product quality with cutting-edge technology.
- Qualifications: 3+ years in software engineering, strong Python and SQL skills required.
The predicted salary is between 60000 - 80000 € per year.
Requirements
- 3+ years of software engineering experience shipping production systems
- Strong proficiency in Python and SQL with the ability to write production-grade, maintainable code
- Experience with big data systems including distributed compute and large-scale storage
- Solid fundamentals in data modeling, system design, and debugging distributed systems
- Experience with AWS and lakehouse ecosystems like Databricks or Spark
- Comfortable with agentic coding workflows and using AI-assisted development tools to iterate faster
- (Desirable) Data engineering background including pipelines, orchestration, and warehousing patterns
- (Desirable) Familiarity with LLM/VLM interfaces, tokenization, structured formats, and multimodal payloads
- (Desirable) Experience with evaluation platforms, experimentation systems, or machine learning infrastructure
- (Desirable) Prior work supporting customer-facing products at scale
What the job involves
- Build the systems and pipelines that enable Search, Product, and other teams to independently access and utilize reliable eval verdicts without bottlenecks
- Take ownership of the "evals-to-product" loop, autonomously determining the best way to turn raw signals into durable datasets that power decision-making across the company
- Build a robust simulator pipeline capable of replaying user interactions with the product in formats legible to LLMs and VLMs, reflecting product changes as they are shipped
- Maintain data trust by implementing monitoring, lineage, and quality checks, ensuring downstream consumers can rely on the results implicitly
- Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality
Member of Technical Staff (Software Engineer, Data Flywheel) in London employer: Deepstreamtech
At Perplexity, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Member of Technical Staff, you'll have the opportunity to work in a dynamic environment where your contributions directly impact product quality and decision-making. We offer competitive benefits, a commitment to employee growth through continuous learning opportunities, and the unique advantage of working with cutting-edge technologies in a small, high-impact team setting.
StudySmarter Expert Advice🤫
We think this is how you could land Member of Technical Staff (Software Engineer, Data Flywheel) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current employees at companies you're eyeing. A friendly chat can sometimes lead to opportunities that aren't even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving Python, SQL, and big data systems. This gives potential employers a taste of what you can do and how you tackle real-world problems.
✨Tip Number 3
Prepare for technical interviews by brushing up on system design and debugging distributed systems. Practice coding challenges and be ready to discuss your thought process. Remember, it's not just about getting the right answer but showing how you approach problems.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight your experience with AWS, data pipelines, and any relevant tools you've used. Let's get you on board!
We think you need these skills to ace Member of Technical Staff (Software Engineer, Data Flywheel) in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your software engineering experience, especially with Python and SQL. We want to see how you've shipped production systems and tackled big data challenges, so don’t hold back on those details!
Tailor Your Application:Take a moment to customise your application for the role. Mention your experience with AWS, Databricks, or Spark, and how you’ve used them in past projects. This helps us see how you fit into our team!
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your experience and skills. Avoid fluff – we want the good stuff!
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, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Deepstreamtech
✨Know Your Tech Inside Out
Make sure you brush up on your Python and SQL skills. Be ready to discuss how you've used these languages in production systems, and prepare to showcase your ability to write maintainable code. Think of specific projects where you’ve tackled big data challenges.
✨Showcase Your Experience with Big Data
Familiarise yourself with distributed compute and large-scale storage systems. Be prepared to talk about your experience with AWS, Databricks, or Spark. Highlight any projects where you’ve built data pipelines or worked with orchestration and warehousing patterns.
✨Demonstrate Problem-Solving Skills
Expect to face questions that test your debugging skills in distributed systems. Prepare examples of how you've approached complex problems in the past, particularly in customer-facing products. This is your chance to show how you can take ownership of the 'evals-to-product' loop.
✨Get Comfortable with AI Tools
Since familiarity with AI-assisted development tools is desirable, be ready to discuss how you've used these tools to enhance your coding workflows. If you have experience with LLM/VLM interfaces or machine learning infrastructure, make sure to highlight that as well!
