Staff Machine Learning Engineer

$177K — $387K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in machine learning, search infrastructure, or distributed systems.
  • Hands-on experience with large-scale search platforms in production.
  • Understanding of information retrieval and knowledge graph concepts.
  • Experience with RAG systems and LLM-based applications in production.
  • Proficiency in languages such as Python, Go, Java, C#, or C++.
  • Familiarity with ML frameworks like PyTorch or TensorFlow and vector databases.
  • Experience with enterprise data systems or multi-tenant SaaS is a plus.

Responsibilities

  • Design and build scalable retrieval systems for unstructured data and hybrid search.
  • Optimize Retrieval-Augmented Generation (RAG) pipelines for AI agents.
  • Develop indexing pipelines to convert enterprise data into retrieval-ready formats.
  • Create ranking and evaluation frameworks to enhance answer quality.
  • Implement permission-aware retrieval for secure access control.
  • Collaborate with product, infrastructure, and research teams to deliver AI capabilities.

Benefits

  • Diverse benefits promoting physical, mental, and emotional health.
  • Support for work-life balance and community contributions.
  • Commitment to a hybrid work environment with flexibility.
Full Job Description

What you can expect

Zoom is building the next generation of Agentic Search — a distributed search foundation that helps AI agents discover, reason over, and act on enterprise knowledge securely and at scale. In this role, you will design and build core search infrastructure for hybrid retrieval across meetings, chat, docs, whiteboards, and third-party enterprise applications. You will work on the system foundations behind keyword search, vector search, metadata filtering, permission-aware retrieval, and low-latency query serving across multi-tenant enterprise data.This is a high-impact opportunity to shape the search platform behind Zoom's AI ecosystem.

Responsibilities:

  • Architecting and implementing scalable search infrastructure for distributed indexing, query execution, result aggregation, vector retrieval, hybrid search, and permission-aware access.

  • Building major components of distributed search and vector database systems, including sharding, replication, rebalancing, recovery, and cluster coordination.

  • Designing and optimize ANN index structures and retrieval algorithms, such as HNSW, IVF, DiskANN-style approaches, quantization, sparse vectors, and filtered vector search

  • Developing storage and indexing pipelines for heterogeneous enterprise data, including segment lifecycle management, compaction, write-ahead logging, and object storage integration.

  • Improving query latency, recall, throughput, cost efficiency, and reliability through rigorous benchmarking, profiling, and systems-level optimization.

  • Partnering closely with product, infrastructure, and applied research teams to ship production-grade AI capabilities.

What we’re looking for:

  • 7+ years of experience building search infrastructure, vector databases, distributed databases, storage engines, or large-scale data platforms in production environments.

  • Strong hands-on experience owning major components of systems similar to Elasticsearch, OpenSearch, Lucene, Solr, Milvus, Qdrant, Vespa, Weaviate, or other distributed search and vector retrieval platforms.

  • Possess understanding of:Information retrieval, Structured query systems, Knowledge graph or graph database concepts

  • Strong understanding of vector search and ANN internals, including HNSW, IVF, PQ/SQ quantization, dense and sparse vector indexes, metadata filtering, and recall/latency trade-offs.

  • Strong system design skills with the ability to reason from first principles about scale, reliability, latency, memory, storage, and cost.

  • Experience operating high-scale, low-latency, multi-tenant infrastructure with clear production ownership.

  • Ability to operate as a senior IC or technical lead, driving ambiguous infrastructure projects from design through production rollout.

Salary Range or On Target Earnings:

Minimum:

$177,100.00

Maximum:

$387,500.00

In addition to the base salary and/or OTE listed Zoom has a Total Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value.

Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience.

We also have a location based compensation structure;  there may be a different range for candidates in this and other locations.

Ways of Working
Our structured hybrid approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting.

Benefits
As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways. Click for more information.

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