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Data Engineer

At World Labs, our mission is to revolutionize artificial intelligence by developing Large World Models, taking AI beyond language and 2D visuals into the realm of complex 3D environments, both virtual and real. We're the team that's envisioning a future where AI doesn't just process information but truly understands and interacts with the world around us.

We're looking for the overachievers, the visionaries, and the relentless innovators who aren't satisfied with the status quo. You know that person who's always dreaming up the next big breakthrough? That's us. And we want you to be part of it.

As a Data Engineer at World Labs, you will be at the forefront of developing AI systems that address critical challenges. We're looking for individuals with strong engineering skills who can contribute to designing, implementing, and optimizing large-scale distributed data pipelines that are powering our state of the art models. We expect these pipelines to encompass data processing and curation as well as selection and serve data to our model training runs. They have to scale to large quantities of data as well as high throughput filters, seeks, and reads. We seek candidates who excel in designing scalable systems and have a deep understanding of the intricacies of data processing in the context of ML workloads. Your work will directly contribute to World Labs' goal of creating AI solutions that have a positive impact on humanity and our planet.

Key Qualifications:

  • Extensive experience in designing data pipelines in the context of large-scale ML model training

  • Expertise in working with the latest and greatest data management and storage framework to implement solutions effectively and with scalability in mind

  • Deep domain knowledge in one or more AI/ML specialties

  • Proven track record of working in teams to train or deploy large models, either at major tech companies or innovative startups

  • Passion for applying AI to solve global challenges

Who You Are:

  1. Fearless Innovator: We need people who thrive on challenges and aren't afraid to tackle the impossible.

  2. Resilient Builder: Impacting Large World Models isn't a sprint; it's a marathon with hurdles. We're looking for builders who can weather the storms of groundbreaking research and come out stronger.

  3. Mission-Driven Mindset: Everything we do is in service of creating the best spatially intelligent AI systems, and using them to empower people.

  4. Collaborative Spirit: We're building something bigger than any one person. We need team players who can harness the power of collective intelligence.

We're hiring the brightest minds from around the globe to bring diverse perspectives to our cutting-edge work. If you're ready to work on technology that will reshape how machines perceive and interact with the world - then World Labs is your launchpad. 

Join us, and let's make history together.

Average salary estimate

$100000 / YEARLY (est.)
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$80000K
$120000K

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What You Should Know About Data Engineer, World Labs

At World Labs, we're changing the game in artificial intelligence, and we're on the hunt for a talented Data Engineer to join our innovative team in San Francisco. At World Labs, we’re not just developing AI — we’re taking it to the next level with Large World Models that understand complex 3D environments. If you’re someone who thrives on innovation and is eager to be part of a transformative journey, this is the perfect opportunity for you. As a Data Engineer, you'll play a pivotal role in designing and optimizing large-scale distributed data pipelines that are essential to our state-of-the-art models. You’ll draw from your strong engineering skills to curate and process massive amounts of data, ensuring these pipelines are efficient and can handle high throughput. For us, it's not just about getting the job done—it's about excelling and pushing the boundaries. We’re looking for someone with extensive experience in ML model training and a solid understanding of modern data management frameworks. Your contributions will directly impact our goal to create AI solutions that benefit humanity and our planet. If you're a fearless innovator with a collaborative spirit, we want you on our team! At World Labs, you’ll find a space to bring your unique perspectives and skills, working alongside brilliant minds to reshape how machines understand and interact with the world. Are you ready to make history together? Join us today!

Frequently Asked Questions (FAQs) for Data Engineer Role at World Labs
What are the main responsibilities of a Data Engineer at World Labs?

As a Data Engineer at World Labs, your primary responsibilities include designing, implementing, and optimizing large-scale distributed data pipelines that enable our advanced AI models to function effectively. You'll be deeply involved in processing and curating data, ensuring that our systems can handle significant quantities with high efficiency. Additionally, you'll collaborate with other teams to ensure seamless integration of data into model training runs, directly contributing to our mission of creating impactful AI solutions.

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What qualifications are required for the Data Engineer position at World Labs?

Candidates for the Data Engineer role at World Labs should possess extensive experience in designing data pipelines specifically for large-scale ML model training. It's essential to have expertise in modern data management frameworks and to understand various AI/ML specialties. A proven track record in collaborative environments, whether at leading tech companies or startups, is crucial. Most importantly, we’re looking for individuals who are passionate about using AI to address global challenges.

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How does the Data Engineer role contribute to World Labs' mission?

The Data Engineer plays a crucial role at World Labs by developing and maintaining the data pipelines that power our Large World Models. These pipelines support critical data processing and curation, necessary for training our AI systems. By ensuring that our models are fed with high-quality and efficiently processed data, you will help us advance our mission of creating AI that has a positive impact on humanity and the planet.

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What skills will help someone succeed as a Data Engineer at World Labs?

To excel as a Data Engineer at World Labs, strong engineering skills are a must, along with expertise in designing scalable data systems. Familiarity with the latest data management and storage frameworks is essential. Additionally, having a deep understanding of machine learning workloads and being a collaborative team player will greatly enhance your effectiveness in this role as you work towards innovative solutions with your colleagues.

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What is the work culture like for a Data Engineer at World Labs?

At World Labs, we pride ourselves on fostering a work culture that values innovation, collaboration, and a mission-driven mindset. As a Data Engineer, you’ll be part of a team that embraces challenges and encourages creative problem-solving. We believe in the power of collective intelligence and strive to create an environment where diverse perspectives are welcomed and encouraged. If you're passionate about making a difference and pushing the boundaries of AI, you’ll thrive here.

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Common Interview Questions for Data Engineer
Can you describe your experience with data pipeline design in the context of machine learning?

When answering this question, focus on providing specific examples of data pipelines you've designed or worked on in the past. Highlight the technologies and processes you used, the scale of the data managed, and how these experiences align with the needs of World Labs.

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How do you ensure data quality and reliability in your data engineering projects?

Discuss the methods you employ to maintain data quality, such as data validation processes, monitoring systems, and error handling techniques. Provide specific strategies you've implemented in past projects to enhance data reliability and integrity.

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What modern data management frameworks are you familiar with, and which do you prefer to use?

Highlight any frameworks you have experience with, such as Apache Kafka, Apache Spark, or cloud services like AWS or Google Cloud. Explain why you prefer certain frameworks over others, referencing their advantages in handling large-scale data processing tasks.

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How do you approach collaboration when working on multi-disciplinary teams?

Illustrate your collaboration style, emphasizing the importance of communication and understanding within diverse teams. Provide examples of successful projects where collaborative efforts led to innovative solutions and highlight how you adapt to different team dynamics.

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What are some challenges you've faced when building data pipelines, and how did you overcome them?

Discuss specific challenges you've encountered, such as scaling issues or data compatibility, and articulate concrete steps you took to resolve those challenges. This reflects your problem-solving skills and ability to adapt under pressure.

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Can you explain your understanding of machine learning workloads and how they influence data pipeline design?

Provide insights into specific machine learning processes and workloads and discuss how these affect data pipeline design. Explain how you would tailor pipelines to support different models and rapidly changing requirements in ML.

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Why is a mission-driven mindset important for a role as a Data Engineer at World Labs?

Express the significance of a mission-driven approach in maintaining motivation and aligning your work with World Labs' goal of creating positive impact through AI. Discuss how your personal mission resonates with this and how it translates into your engineering practices.

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What strategies do you use for optimizing data processing performance?

Outline specific optimization techniques you’ve applied, including caching strategies, data partitioning, and efficient algorithm choices. Include examples of measurable improvements in processing speed or throughput resulting from these optimizations.

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How do you stay updated with the latest trends and technologies in data engineering and machine learning?

Discuss your dedication to continuous learning. Mention resources like webinars, technical blogs, online courses, and participation in conferences that you engage in to stay current in the rapidly evolving fields of data engineering and ML.

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What inspired you to pursue a career in data engineering, particularly within AI?

Share your personal journey into data engineering, focusing on what excites you about working with AI specifically. Discuss any particular role models, experiences, or breakthroughs in AI that inspired your career path.

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DATE POSTED
December 3, 2024

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