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Vector Databases Jobs in Redmond, WA (NOW HIRING)

Chewy

Software Engineer III, Discovery

Bellevue, WA · On-site

$141K - $225K/yr

Understanding of LLM architectures, embeddings, and vector databases (e.g., Qdrant, Pinecone, Milvus, FAISS). * Demonstrated ability to drive cross-team technical initiatives and influence ...

Chewy

Software Engineer III, Discovery

Bellevue, WA · On-site +1

$141K - $225K/yr

Understanding of LLM architectures, embeddings, and vector databases (e.g., Qdrant, Pinecone, Milvus, FAISS). * Demonstrated ability to drive cross-team technical initiatives and influence ...

STRAC

Senior Software Engineer

Bellevue, WA

$138K - $182K/yr

Hands-on experience using AI/ML tools (e.g., OpenAI, Hugging Face, LangChain, vector databases) and integrating AI into production systems * Strong understanding of AI/ML concepts such as LLMs ...

Stoke Space

Senior AI Software Engineer

Kent, WA · On-site +1

$154K - $231K/yr

Build and maintain RAG pipelines leveraging vector databases to enable intelligent search and retrieval * Develop comprehensive evaluation frameworks (evals) to measure, monitor, and improve AI ...

STRAC

Senior Software Engineer

Seattle, WA

$139K - $183K/yr

Hands-on experience using AI/ML tools (e.g., OpenAI, Hugging Face, LangChain, vector databases) and integrating AI into production systems * Strong understanding of AI/ML concepts such as LLMs ...

Belva.ai

Software Engineer II

Bellevue, WA · On-site

You will play a central role in designing and developing how our products use ML technologies such as transformers, vector databases, etc. The ideal candidate should have at least 3 years of ...

The Mutual Group

Lead AI Engineer - AWS Platform

Seattle, WA · On-site +1

$130K - $190K/yr

Build RAG pipelines using vector databases and enterprise data sources * Build machine learning models that automate their training, validation, monitoring, and retraining * Develop APIs and services ...

Trunk Tools

AVP, Global Talent Acquisition

Redmond, WA · On-site

... by vector databases. Our zero-distance innovation solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster. Our mission is to bridge the gap between AI ...

Tessera Labs

Software Engineer, Backend

Seattle, WA · On-site

... servers, vector databases, and automation workflows. • Enable smooth data exchange between AI agents and enterprise systems like Salesforce, SAP, and Workday. • Identify and fix performance ...

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Showing results 1-20

All JobsVector Databases JobsVector Databases Jobs in Redmond, WA

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.
What job categories do people searching Vector Databases jobs in Redmond, WA look for? The top searched job categories for Vector Databases jobs in Redmond, WA are:
What cities near Redmond, WA are hiring for Vector Databases jobs? Cities near Redmond, WA with the most Vector Databases job openings:
Vector Databases jobs near you
Infographic showing various Vector Databases job openings in Redmond, WA as of June 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.
Senior Manager, Software Development - GPU Accelerated Storage

Senior Manager, Software Development - GPU Accelerated Storage

Nvidia

Seattle, WA

Full-time

Posted 27 days ago

Job description

NVIDIA data center systems have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. These platforms bring together the full power of NVIDIA GPUs/CPUs, NVIDIA NVLink, NVIDIA Networking, and a fully optimized NVIDIA AI and HPC software stack.

We're seeking a leader for our Data Center Storage Acceleration & Platforms team. In this role, you'll optimize NVIDIA platforms to accelerate storage access-eliminating bottlenecks by enabling direct data paths for transfers between GPU memory and storage, bypassing the CPU when possible. You'll collaborate with leaders across NVIDIA to define reference storage platform designs that integrate NVIDIA-accelerated computing into enterprise storage systems, enabling optimized data handling and delivery.

What you'll be doing:

  • Look across the platform, from applications and frameworks to drivers and firmware - to identify software and hardware opportunities that accelerate storage performance. This includes developing new driver features, C++/CUDA libraries, and removing performance & power bottlenecks.

  • Drive alignment of the storage acceleration roadmap across next-generation systems, frameworks, applications, and the broader storage ecosystem.

  • Spokesperson for the global team, championing initiatives both internally and externally.

  • Lead and coordinate the planning, scheduling, and carrying out of team projects and deliverables, ensuring successful completion and accountability for the global team.

  • Contribute to the planning and execution of NVIDIA's reference storage platforms.

What we need to see:

  • Deep knowledge of data storage platforms, databases, vector databases.

  • In-depth understanding of NVMe, high performance RDMA network protocols, and related technologies.

  • Deep understanding of system level architecture, such as topologies, interconnects, memory hierarchy, interrupts, and memory-mapped IO.

  • Strong interpersonal, verbal and written communications skills.

  • Successful experience leading team with numerous complex products, competing priorities, and successful delivery on the mission.

  • Bachelor's or preferably Master's or Doctoral (Ph.D) degree or equivalent experience in Computer Science, Electrical Engineering, or a related field.

  • 12+ overall years in the industry, including 6+ years growing, mentoring and managing teams with similar responsibilities.

Ways to stand out from the crowd:

  • Development experience in storage software such as key-value storage, file systems, object storage systems and vector databases.

  • Knowledge of operating system development, including thread and process management, virtual and device memory (e.g., dmabuf), and user-level network and storage I/O.

  • Experience in CUDA programming, exceptional C/C++ programming skills.

  • Previous experience working with system software for accelerators such as GPUs, DPUs, or FPGAs.

  • Internals of frameworks like PyTorch and JAX.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, passionate and self-motivated, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 248,000 USD - 391,000 USD for Level 4, and 292,000 USD - 442,750 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 12, 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.
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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