Solutions Architect, Zilliz
NYC Metro Area
+ Bonus + Equity
Vector database for production-ready AI
Open for applications
Vector database for production-ready AI
101-200 employees
Open for applications
+ Bonus + Equity
101-200 employees
Company mission
To democratize AI, Zilliz is committed to simplifying data management for AI applications and making vector databases accessible to every organization.
Role
Who you are
- Bachelor's degree or above in Computer Science, Information Technology, or related field
- Over 5 years of experience in infrastructure software pre-sales, development, or consulting
- Good understanding of the following areas: Cloud-native, Database, and Machine Learning
- Good understanding of open source and experience with an open-source community is ideal
- A team player who is optimistic, integral, responsible, good at communicating, and willing to help other colleagues
- A passionate learner and a powerful problem-solver with decisiveness
- Coding experience in Python, Node.js, Go, or Java
- We hope you can adapt to a fast-changing environment (i.e. the different stages of a startup company)
What the job involves
- Drive technical engagements with key customers to deliver quality technical solutions and services
- Establish repeatable motions and best practices to improve the efficiency of customer projects. Build technical resources such as tutorials, white papers, and tools to address customer needs
- Play an active role in the open-source community. Work as a community technical expert and keep your influence by actively joining all types of community activities and events
- Build long-term strategic relationships with potential clients and identify new opportunities in the user community
- Responsible for communicating with key users/clients and providing them with help throughout the whole process of trial, testing, and delivering a full solution in production
Our take
Vector databases have become essential for powering advanced AI applications, which demand high recall, low latency, and robust throughput. Zilliz has positioned itself at the forefront of this field with its vector database management system, Milvus.
Building on its initial success, Zilliz recently released Milvus 2.4m which significantly enhances vector search capabilities. This latest version introduced GPU indexing, leveraging NVIDIA's CUDA-Accelerated Graph Index for Vector Retrieval (CAGRA) which outperforms traditional CPU-based indexes like HNSW.
Zilliz's commitment to innovation is further demonstrated by the expansion of its Hybrid Search capabilities, including a beta version of sparse vector embeddings for more accurate and semantically rich searches. These advancements, along with the evolution of Zilliz Cloud, emphasise the company's dedication to pushing the boundaries of what vector databases can achieve and make the future of the company an exciting one.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Aug 2022
$60m
SERIES B
Nov 2020
$43m
SERIES B
Total funding: $113m
Company benefits
- Equity
- Regular bonus and equity refresh opportunities
- Comprehensive medical, dental, and vision insurance
- Paid time off, including vacation, bereavement, and sick days
- Generous 401(k) and regional retirement plans
- Hybrid work model/Remote work opportunities available
Company values
- Mission Driven: We dedicate oursevles to serving something beyond ourselves. We solve for the customer and bring value to the global engineering community
- Aim Higher: High standards are the basis for building trusting relationships. Always execute with excellence
- Bias for Action: We trigger action based on thoughtful consideration. We focus on the goals, process and results of our actions
- Altruism: Bring out our best, let go of egos, and work with empathy and trust to achieve great things together
Company HQ
Centennial, Redwood City, CA
Articles
Leadership
Charles Xie
(CEO)Previously worked as a Senior Software Engineer at Oracle, before creating The Milvus Project. Serves on the governing board of the LF AI & Data Foundation.
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