Software Engineer / Researcher, AI-Native database systems

Position Overview

Based in San Jose and part of the Infrastructure team, you will join ByteDance’s database R&D group to build and own cutting‐edge database products. In this role, you’ll contribute to developing next‐generation AI-native database systems—intelligent, multimodal, and designed for the era of large models—powering products like TikTok, CapCut, and more. The position offers a dynamic and innovative environment that values intellectual curiosity, self-direction, and strong system-level design and coding skills.

Employment Type: Regular | Job Code: A167658

Key Responsibilities

• Architect and implement AI-native databases that seamlessly integrate structured, unstructured, and vectorized data.
• Design storage engines optimized for embedding ingestion, multimodal retrieval, and real-time AI interaction.
• Build scalable and distributed vector search systems with low-latency guarantees.
• Develop AI-augmented query processors that leverage large language models (LLMs) for semantic parsing, intent understanding, and cost estimation.
• Collaborate on developing retrieval-augmented generation (RAG) infrastructure and LLM agent memory backends.
• Drive innovations in learned index structures, self-optimizing databases, and AI-integrated transaction systems.
• Publish and contribute to broader research and open-source communities.

Required Qualifications

• Bachelor’s, Master’s, or Ph.D. in Computer Science or related fields with strong systems or AI research experience.
• 2+ years in core database systems, large-scale distributed infrastructure, or machine learning systems.
• Strong coding and system-level design skills in C++ / Rust / Go.
• Deep expertise in one or more areas: storage engine architecture (LSM-trees, column stores, HTAP systems); vector retrieval systems, similarity search, and ANN indexing; AI infra or model-serving infrastructure (for embeddings / RAG / LLMs); or semantic search, agent systems, and AI-native memory frameworks.
• Ability to collaborate across research, engineering, and product teams to translate ideas into production systems.

Preferred Qualifications

• Experience with open-source systems such as Faiss, Milvus, DuckDB, ClickHouse, TiKV, or RocksDB.
• Publications at top-tier conferences (e.g., SIGMOD, VLDB, NeurIPS, MLSys, ICDE).
• Familiarity with GCP, AWS, or Azure’s database and AI integration strategies.
• Prior contributions to RAG, memory-augmented models, or self-tuning database components.

Benefits & Perks

• Compensation: Base salary range of $136,800 - $359,720 annually; may include additional bonuses, restricted stock units and other incentives.
• Day one access to medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave, short-term and long-term disability coverage, and life insurance.
• Wellbeing benefits, 10 paid holidays, 10 paid sick days, and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).