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Dettagli dell’opportunità

Next-Generation Data Systems

Tipo di posizione
Ricercatore
Data di pubblicazione
October 19, 2026
Dipartimento
Accelerated Systems & Data Platforms
Area di ricerca
Accelerated Systems & Data Platforms
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Descrizione del progetto

Research Engineers / Research Scientists
Next-Generation Data Systems
Ref. 2025_016

About the Roles
At IBM Research Zurich, we are expanding our team with multiple engineers and researchers to build the next generation of large-scale data systems that support both modern data workloads and traditional enterprise workloads.Our goal is to design platforms capable of executing complex queries and workflows efficiently across heterogeneous engines, storage layers, and hardware.

We focus on core systems challenges such as query optimization, cross-engine query routing, serverless scheduling and resource management. These systems must support diverse workloads while delivering strong performance, scalability, and reliability.

Our work combines systems research and production engineering, and many of the technologies we develop become part of products and open-source platforms used at scale.

What You Will Do
You will design and build core components of next-generation data platforms. Much of this work happens deep in the system stack, including query execution engines, schedulers, and distributed resource management layers. Depending on your interests and background, your work may focus more on systems engineering, systems research, or a combination of both.

What we are looking for
We are looking for engineers or scientists who enjoy working deep in the stack, designing and building the infrastructure that powers large-scale data processing systems.

You are comfortable reasoning about query execution plans, distributed scheduling, resource management, and systems performance. You enjoy understanding how complex systems behave at scale and improving them. You are curious about how modern workloads—including multimodal data processing and agent-based workflows—should influence the architecture and behavior of next-generation data systems.

Minimum Qualifications

Master’s degree in Computer Science, Distributed Systems, Databases, or related field, or equivalent industry experience
Strong experience building distributed systems or large-scale infrastructure software
Excellent programming skills in C++, Java, or Scala
Experience working with large-scale data processing frameworks or query engines (e.g., Spark, Presto/Trino, Flink)
Experience designing or applying optimization techniques for complex systems, using analytical methods, heuristics, or machine learning

Preferred Qualifications

Experience working on query engines, query optimizers, or execution runtimes
Experience building distributed schedulers or resource managers
Familiarity with serverless or elastic compute architectures
Experience working with columnar data formats and table formats (Parquet, Arrow, Iceberg)
Experience contributing to large open-source systems
Interest in applying ML or analytical models to improve system performance (e.g., cost models, scheduling policies)
Experience with hardware acceleration for data processing, such as GPUs, vectorized execution, SIMD, or specialized accelerators
PhD in Computer Science or a related field is a plus

Why Join Us

Work on systems that ship in products and open-source projects used at scale
Collaborate with a global team across Europe, Africa, US, and India
Influence the architecture of next-generation data platforms
Access real-world workloads and cutting-edge infrastructure

Diversity

IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable all genders to strike the desired balance between their professional development and their personal lives.

How to apply

Please submit you application with a cover letter and curriculum vitae through the link below.

Apply


Contatto accademico

Accelerated Systems & Data Platforms
Last Update IBM Research Europe – Zurich Lab zurich.ibm.com
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