Member of Engineering (Pre-training / Data Acquisition)

Member of Engineering (Pre-training / Data Acquisition)

Trainee 60000 - 80000 € / year (est.) Home office possible
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At a Glance

  • Tasks: Join our team to build cutting-edge web crawlers for AI data acquisition.
  • Company: Poolside, a pioneering company in Artificial General Intelligence.
  • Benefits: Enjoy fully remote work, flexible hours, and generous vacation time.
  • Other info: Collaborative culture with a focus on well-being and continuous learning.
  • Why this job: Make a real impact on the future of AI and software development.
  • Qualifications: Experience in distributed systems and large-scale data extraction is essential.

The predicted salary is between 60000 - 80000 € per year.

ABOUT POOLSIDE

In this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers.

Poolside exists to be this company: to build a world where AI will be the engine behind economically valuable work and scientific progress. We believe the fastest way to reach AGI lies in accelerating software development itself, by reshaping the developer experience with agentic systems, coding assistants, and the frontier models that power them. We deploy these systems directly into the development environments of security-conscious enterprises.

ABOUT OUR TEAM

We were founded in the US and have our home there, but our team is distributed across Europe and North America. We get our fix of in-person collaboration (and croissants) in Paris each month for 3 days, always Monday-Wednesday, with an open invitation to stay the whole week. We also do longer off-sites once a year.

Our team is a multidisciplinary blend of research, engineering, and business experts. What unites us is our deep care for what we build together. We’re in a race that requires hard work, intellectual curiosity, and obsession; to balance this intensity, we’ve assembled a team of low ego and kind-hearted individuals who have built the special culture Poolside has. By building collaboratively and with intention, we create a compounding effect that moves the entire company forward towards our mission: reaching AGI through intelligence systems built for software development.

ABOUT THE ROLE

You'll be working alongside our pre-training data team, focused on one of the most foundational challenges in training frontier LLMs: acquiring the best possible pre-training data. The data we collect is upstream of everything. It directly shapes the capability of the models we train. As our first dedicated data acquisition engineer, you will spearhead and evolve systems that crawl the web at massive scale, rapidly ingest data from strategic partnerships, and build specialized tooling to maximize recall from high-value sources. You'll collaborate closely with pre-training data researchers and engineers to ensure that our sourcing of data maps to our training needs, to ensure we have the most capable pre-trained models.

YOUR MISSION

To deliver the highest-quality, diverse, and most comprehensive data corpus to fuel the pre-training of frontier models for software development.

RESPONSIBILITIES

  • Design, build, and operate a large-scale web crawler responsible for acquiring all openly accessible data on the internet
  • Develop specialized deep crawlers targeting high-value sources to improve recall and coverage
  • In collaboration with data researchers, own a long-term road map for data acquisition
  • Build observability, monitoring, and debugging tooling to ensure reliability and transparency across crawl infrastructure
  • Collaborate with pre-training, post-training, and evaluations teams to align data acquisition priorities with model training needs
  • Build high-throughput ingestion pipelines for rapidly onboarding partner data and evaluating it for quality

SKILLS & EXPERIENCE

  • Strong distributed systems background with proven experience building and operating large-scale infrastructure — data pipelines, web crawlers, or similar
  • Proficiency in Python, and comfortable optimizing performance and debugging complex systems under production conditions
  • Hands-on experience with web crawling or large-scale data extraction: understanding of HTTP protocols, distributed job queues, and data parsing at scale
  • Familiarity with cloud platforms (AWS) and container orchestration (Kubernetes, Docker) for deploying and managing high-throughput workloads
  • Awareness of the non-technical dimensions of internet-scale crawling: data privacy, robots.txt adherence, and responsible crawl practices
  • Nice to have: Prior experience pre-training LLMs
  • Experience in building trillion-scale SOTA pre-training datasets
  • Experience translating research to production at scale

PROCESS

  • Intro call with one of our Founding Engineers
  • Technical Interview(s) with one of our Members of Engineering
  • Team fit call with the People team
  • Final interview with one of our Founding Engineers

BENEFITS

  • Fully remote work & flexible hours
  • 37 days/year of vacation & holidays
  • 16 weeks of flexible, full-pay parental leave
  • Health insurance allowance for you & dependents
  • Company-provided equipment
  • Well-being, always-be-learning & home office allowances
  • Frequent team get togethers
  • Diverse & inclusive people-first culture

Member of Engineering (Pre-training / Data Acquisition) employer: poolside

Poolside is an exceptional employer that champions innovation and collaboration in the pursuit of Artificial General Intelligence. With a fully remote work model, flexible hours, and generous benefits including 37 days of vacation and comprehensive health insurance, we foster a supportive and inclusive culture that prioritises employee well-being and growth. Our unique monthly team gatherings in Paris and annual off-sites create a vibrant community where talented individuals can thrive and contribute to groundbreaking advancements in AI.

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Contact Detail:

poolside Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Member of Engineering (Pre-training / Data Acquisition)

Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those at Poolside. Use LinkedIn or even Twitter to connect with current employees and ask about their experiences. A friendly chat can sometimes lead to opportunities that aren’t even advertised!

Tip Number 2

Show off your skills! If you’ve got a portfolio or any projects related to data acquisition or web crawling, make sure to highlight them. Share your GitHub or any relevant work during interviews to demonstrate your hands-on experience.

Tip Number 3

Prepare for the technical interview by brushing up on your Python skills and understanding distributed systems. Practice coding challenges that focus on data pipelines and web crawlers. The more prepared you are, the more confident you’ll feel!

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Poolside team. Let’s get you on board!

We think you need these skills to ace Member of Engineering (Pre-training / Data Acquisition)

Distributed Systems
Large-Scale Infrastructure
Data Pipelines
Web Crawlers
Python
Performance Optimisation
Debugging Complex Systems

Some tips for your application 🫡

Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI and software development shine through. We want to see that you’re not just looking for a job, but that you genuinely care about the mission of reaching AGI and how your skills can contribute to that.

Tailor Your Experience:Make sure to highlight your relevant experience in building large-scale systems or data pipelines. We love seeing specific examples of your work, especially if it relates to web crawling or data acquisition. This helps us understand how you can fit into our team.

Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it's necessary. Make it easy for us to see your qualifications and how they align with the role of Data Acquisition Engineer.

Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it helps us keep everything organised on our end.

How to prepare for a job interview at poolside

Know Your Tech Inside Out

Make sure you brush up on your knowledge of distributed systems, web crawling, and data pipelines. Be ready to discuss your hands-on experience with Python and any large-scale infrastructure you've built or operated. This role is all about technical prowess, so show them you know your stuff!

Understand the Company’s Mission

Dive deep into Poolside's mission to reach AGI through software development. Familiarise yourself with their approach to data acquisition and how it impacts model training. When you can connect your skills to their goals, it shows genuine interest and alignment with their vision.

Prepare for Technical Challenges

Expect to face some technical challenges during the interview. Practice solving problems related to data extraction, HTTP protocols, and cloud platforms like AWS. Being able to think on your feet and demonstrate your problem-solving skills will impress the interviewers.

Show Your Collaborative Spirit

Poolside values a low-ego, kind-hearted culture. Be prepared to discuss how you've collaborated with teams in the past, especially in multidisciplinary settings. Highlight your ability to work closely with researchers and engineers to align data acquisition with training needs.