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Vector Databases Jobs in Pleasanton, CA (NOW HIRING)

Zilliz

Solutions Architect - SF Bay Area

Redwood City, CA · On-site

$250K - $285K/yr

Zilliz is a fast-growing startup developing the industry's leading vector database for enterprise-grade AI. Founded by the engineers behind Milvus, the world's most popular open-source vector ...

Zilliz

Solutions Architect - SF Bay Area

Redwood City, CA · On-site

$250K - $285K/yr

Zilliz is a fast-growing startup developing the industry's leading vector database for enterprise-grade AI. Founded by the engineers behind Milvus, the world's most popular open-source vector ...

CosQube INC

ML/AI Engineers

Santa Clara, CA · On-site

Vector databases, embedding systems, model deployment, MLOps * Anomaly Detection: AIOps platforms, time-series analysis, observability systems * Previous Experience: HAL projects or similar ML ...

E-Solutions, Inc.

Python Engineer

San Jose, CA · On-site

... databases. - Experience with Vector Databases (e.g., Pinecone, Weaviate). - Proficient with Docker, AWS/Google Cloud Platform cloud platforms, and asynchronous task queues. Other Requirements ...

Fortinet, Inc.

AI Test Engineer

Santa Clara, CA · On-site

$100K - $140K/yr

Support RAG pipelines, including vector databases and hybrid search * Integrate agents with external tools, APIs, and business systems * Run LLM/RAG evaluations to identify issues and improve ...

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Vector Databases information

What are vector databases?

Vector databases are specialized databases designed to store, manage, and search high-dimensional vector data, which is commonly generated from machine learning models, such as embeddings from natural language processing or image recognition. They enable efficient similarity search operations, such as finding the most similar items to a given query vector, which is essential for applications like recommendation systems, semantic search, and AI-powered search engines. Unlike traditional databases that handle structured or unstructured data, vector databases are optimized for fast and scalable similarity searches on large datasets of vectors.

What are some common challenges faced when working with vector databases, and how can they be addressed?

Professionals working with vector databases often encounter challenges such as efficiently scaling to handle large datasets, ensuring low-latency similarity searches, and integrating the database with machine learning pipelines. To address these, teams typically implement distributed architectures, fine-tune indexing strategies, and collaborate closely with data engineers and machine learning specialists. Staying updated with the latest developments in vector database technologies and maintaining clear communication with cross-functional teams are also key to overcoming these challenges.

What is the difference between Vector Databases vs Data Engineers?

AspectVector DatabasesData Engineers
Required SkillsDatabase management, data modeling, query optimizationData pipeline development, ETL processes, programming
Work EnvironmentData storage systems, AI/ML projects, cloud platformsData infrastructure, cloud environments, big data tools
Industry UsageAI, machine learning, recommendation systemsData integration, analytics, data architecture

While Vector Databases focus on storing and querying high-dimensional vector data for AI applications, Data Engineers build and maintain data pipelines and infrastructure to support data analysis and machine learning workflows. Both roles are essential in data-driven industries but serve different functions within the data ecosystem.

What are the key skills and qualifications needed to thrive as a vector database engineer, and why are they important?

Success as a Vector Database Engineer requires a strong background in computer science, database management, and experience with machine learning or AI-driven data systems. Familiarity with vector database platforms (such as Pinecone, Milvus, or Weaviate), cloud infrastructure, and proficiency in languages like Python are typically expected. Strong problem-solving skills, effective communication, and the ability to work cross-functionally help engineers stand out. These competencies are vital to efficiently design, deploy, and maintain scalable vector search solutions that power modern AI applications.
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What job categories do people searching Vector Databases jobs in Pleasanton, CA look for? The top searched job categories for Vector Databases jobs in Pleasanton, CA are:
What cities near Pleasanton, CA are hiring for Vector Databases jobs? Cities near Pleasanton, CA with the most Vector Databases job openings:
Vector Databases jobs near you
Infographic showing various Vector Databases job openings in Pleasanton, CA as of July 2026, with employment types broken down into 66% Full Time, and 34% Contract. Highlights an 92% In-person, and 8% Remote job distribution.

Senior Software Engineer, AI Storage

Nvidia Corporation

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Re-posted 19 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies

Job description

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company." We're looking to grow our company and establish teams with the most inquisitive people in the world. Join us at the forefront of technological advancement.
What you'll be doing:
  • Work on first solutions in the industry that bring exceptional performance and security improvements to the infrastructure used by leading applications.
  • Develop new features and enable various technologies around data storage for GPU IO.
  • Develop advanced C++/CUDA libraries and algorithms for speed-of-light performance
  • Remove performance bottlenecks by coming up with optimization(s) in the IO stack, frameworks, and applications.
  • Work collaboratively with other specialists including the research teams and be willing to take on complex engineering tasks that progress towards the goals of the team and the company.

What we need to see:
  • Good knowledge of Linux kernel internals, Filesystem, Object storage systems, Databases, Vector Databases
  • Good understanding of NVMe and related technologies
  • Development experience in Cloud, Virtualization (VMware, KVM), Container technologies.
  • Advanced knowledge in Computer Architecture
  • Solid understanding in data structures and algorithms
  • Bash and Python experience
  • Excellent communication and planning skills.
  • BS or MS or PhD in computer science or a related field or equivalent experience.
  • 7+ years of strong coding experience using C, C++, Rust, Python

Ways to stand out from the crowd:
  • Development experience in storage software such as Key-Value, File systems object storage systems, Vector Databases
  • Internals of frameworks like PyTorch, JAX
  • Exceptional CUDA programming skills. Exceptional C++ programming skills

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and dedicated people on the planet working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 6, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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