Machine Learning Data Engineer - Systems & Retrieval

Zyphra is an artificial intelligence company based in Palo Alto, California.

The Role :

As a Machine Learning Data Engineer - Systems & Retrieval , you will build and optimize the data infrastructure that fuels our machine learning systems. This includes designing high-performance pipelines for collecting, transforming, indexing, and serving massive, heterogeneous datasets from raw web-scale data to enterprise document corpora. You’ll play a central role in architecting retrieval systems for LLMs and enabling scalable training and inference with clean, accessible, and secure data. You’ll have an impact across both research and product teams by shaping the foundation upon which intelligent systems are trained, retrieved, and reasoned over.

You’ll work across :

Design and implementation of distributed data ingestion and transformation pipelines

Building retrieval and indexing systems that support RAG and other LLM-based methods

Mining and organizing large unstructured datasets, both in research and production environments

Collaborating with ML engineers, systems engineers, and DevOps to scale pipelines and observability

Ensuring compliance and access control in data handling, with security and auditability in mind

Requirements :

Strong software engineering background with fluency in Python

Experience designing, building, and maintaining data pipelines in production environments

Deep understanding of data structures, storage formats, and distributed data systems

Familiarity with indexing and retrieval techniques for large-scale document corpora

Understanding of database systems (SQL and NoSQL), their internals, and performance characteristics

Strong attention to security, access controls, and compliance best practices (e.g., GDPR, SOC2)

Excellent debugging, observability, and logging practices to support reliability at scale

Strong communication skills and experience collaborating across ML, infra, and product teams

Bonus Skill Set :

Experience building or maintaining LLM-integrated retrieval systems (e.g, RAG pipelines)

Academic or industry background in data mining, search, recommendation systems, or IR literature

Experience with large-scale ETL systems and tools like Apache Beam, Spark, or similar

Familiarity with vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding-based retrieval

Understanding of data validation and quality assurance in machine learning workflows

Experience working on cross-functional infra and MLOps teams

Knowledge of how data infrastructure supports training pipelines, inference serving, and feedback loops

Comfort working across raw, unstructured data, structured databases, and model-ready formats

Why Work at Zyphra :

Our research methodology is to make grounded, methodical steps toward ambitious goals. Both deep research and engineering excellence are equally valued

We strongly value new and crazy ideas and are very willing to bet big on new ideas

We move as quickly as we can; we aim to minimize the bar to impact as low as possible

We all enjoy what we do and love discussing AI

Benefits and Perks :

Comprehensive medical, dental, vision, and FSA plans

Competitive compensation and 401(k)

Relocation and immigration support on a case-by-case basis

On-site meals prepared by a dedicated culinary team; Thursday Happy Hours

In-person team in Palo Alto, CA, with a collaborative, high-energy environment

If you're excited by the challenge of high-scale, high-performance data engineering in the context of cutting-edge AI, you’ll thrive in this role. Apply Today!

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