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ZA
Data Infrastructure Intern (Summer 2025)
zaimlerSan Mateo, United StatesinternshipVerifiedPosted 27 Nov 2024
About the role
About Us
We are on a mission to bridge the gap between enterprise business knowledge and data, democratizing data discovery and curation to prepare organizations for the era of generative AI. Today's data tools are overly complex, poorly integrated, and siloed, forcing AI Practitioners and data scientists alike to spend more time wrestling with tools, relying on tribal knowledge, and navigating data lakes rather than doing meaningful data science work. The current landscape of data tools and processes is heavily manual and needs to catch up with the vast amount of data generated daily. With the advent of Gen AI and multi-modality, this challenge has only grown more complex and broken.
Backed by top VC funds, we are committed to making enterprise data AI-ready faster, more reliably, and with a stronger foundation of factual semantic knowledge. This leads to more accurate models, superior outcomes, and better business results. Our team of seasoned data infrastructure and machine learning experts (from LinkedIn, Visa, Truera, Hive, and Branch) has spent the past two decades building bespoke systems to solve these very challenges.
Join our growing team of ML research and data infrastructure experts. We're committed to empowering AI and data scientists to seamlessly integrate semantic learning with generative AI. Be part of our journey to shape the future of enterprise AI.
About the Job
We are looking for a few interns to join us either part-time through the year or Full-time for the summer. The ideal candidate should have interest and some experience in Distributed Computing and Data Systems. In this internship, you'll play a critical part in developing distributed systems, optimizing data pipelines, and collaborating with machine learning experts to tackle real-world challenges in AI/ML operations.
We are on a mission to bridge the gap between enterprise business knowledge and data, democratizing data discovery and curation to prepare organizations for the era of generative AI. Today's data tools are overly complex, poorly integrated, and siloed, forcing AI Practitioners and data scientists alike to spend more time wrestling with tools, relying on tribal knowledge, and navigating data lakes rather than doing meaningful data science work. The current landscape of data tools and processes is heavily manual and needs to catch up with the vast amount of data generated daily. With the advent of Gen AI and multi-modality, this challenge has only grown more complex and broken.
Backed by top VC funds, we are committed to making enterprise data AI-ready faster, more reliably, and with a stronger foundation of factual semantic knowledge. This leads to more accurate models, superior outcomes, and better business results. Our team of seasoned data infrastructure and machine learning experts (from LinkedIn, Visa, Truera, Hive, and Branch) has spent the past two decades building bespoke systems to solve these very challenges.
Join our growing team of ML research and data infrastructure experts. We're committed to empowering AI and data scientists to seamlessly integrate semantic learning with generative AI. Be part of our journey to shape the future of enterprise AI.
About the Job
We are looking for a few interns to join us either part-time through the year or Full-time for the summer. The ideal candidate should have interest and some experience in Distributed Computing and Data Systems. In this internship, you'll play a critical part in developing distributed systems, optimizing data pipelines, and collaborating with machine learning experts to tackle real-world challenges in AI/ML operations.
What You Will be Doing
- Assist in building and optimizing scalable data systems to process enterprise data.
- Support the development of APIs and infrastructure powering our AI/ML platform.
- Collaborate with engineers to improve system performance, reliability, and scalability.
- Participate in testing and debugging distributed systems in production environments
Prior Experience
- A current student or recent graduate in Computer Science, Data Engineering, or a related field.
- Startup internship experience is highly preferred
- Knowledgeable in programming languages like Python, Java, or Go.
- Strong background in the fundamentals of distributed computing
- Great communication skills and a team player
- Willingness to learn
Nice to Haves
- Experience with tools such as Kafka, Ray, or Kubernetes.
- Interest in AI/ML systems or large-scale data challenges.
- Prior work with event-driven or stateful workflow systems.
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