Contribute to AI/agentic capabilities: LLM pipelines, agent observability, intelligent data modeling.
Take part in design reviews, and learn from code reviews and design pairing with senior engineers.
Write high-quality, well-tested code and follow CI/CD best practices.
Partner with Product and cross-regional engineering teams to translate business needs into scalable solutions.
Communicate technical ideas and tradeoffs clearly in English.
Who You Are
PhD (new graduates welcome) in distributed systems, AI/ML, or mathematics / applied mathematics / statistics from a top university, or an outstanding Master’s graduate with published papers at top venues in systems, databases, algorithms, or statistics.
Good understanding of engine internals (query engines, storage engines, stream processing, distributed systems), or deep mathematical and algorithmic strength (e.g., optimization, probability, statistics, algorithm design) that you can apply to data systems, demonstrated through research, publications, open-source contributions, or hands-on experience with big data stacks such as Spark, ClickHouse, Druid, and Kafka.
Familiarity with LLM and AI agent systems, and eagerness to build with them.
Proficient in at least one of Python, Go, Java, Scala, or Rust.
Actively uses AI coding tools (Cursor, Claude Code, GitHub Copilot) in daily work.
Curious, self-driven, and comfortable with ambiguity; able to work with distributed teams across time zones.
Excellent English communication skills, both verbal and written.
Bonus Points
Publications at top systems/database venues (VLDB, SIGMOD, OSDI, SOSP, EuroSys, ATC), or top algorithms/ML/statistics venues.
Meaningful contributions to Apache big data projects.
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