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Vector Databases Jobs in Detroit, MI (NOW HIRING)

Hearst

Full-Stack Data Engineer

Troy, MI

Experience with LLMs, Machine Learning & Deep Learning Libraries, AI Application Frameworks, Vector Databases * Experience with Automotive Data / Industry * Experience with Agile / Scrum Primary ...

Hearst Newspapers

Full-Stack Data Engineer

Troy, MI

Experience with LLMs, Machine Learning & Deep Learning Libraries, AI Application Frameworks, Vector Databases * Experience with Automotive Data / Industry * Experience with Agile / Scrum Primary ...

Jackson Dawson

Senior Software Engineer

Dearborn, MI · On-site

$112K - $148K/yr

Experience with RAG architectures and vector databases * Background in financial analytics or B2B SaaS products * Experience with LLMOps (e.g., LangFuse, evaluation frameworks, hallucination ...

Ford Motor Company

AI Software Engineer

Dearborn, MI · On-site

Experience with vector search, hybrid retrieval architectures, or vector databases (Chroma, Qdrant, Pinecone, pgvector). * Experience working with GCP services (Vertex AI, Cloud Run, and BigQuery) or ...

Waltonen

C++ / Python Programmer

Warren, MI · On-site

Familiarity with Retrieval-Augmented Generation (RAG), Vector databases, Cloud platforms, Docker/containerized environments. * Experience in manufacturing, defense, automotive, or industrial ...

Waltonen

AI Programmer

Warren, MI · On-site

Familiarity with Retrieval-Augmented Generation (RAG), Vector databases, Cloud platforms, Docker/containerized environments * Experience in manufacturing, defense, automotive, or industrial ...

Waltonen

C++ / Python Programmer

Warren, MI · On-site

Familiarity with Retrieval-Augmented Generation (RAG), Vector databases, Cloud platforms, Docker/containerized environments. * Experience in manufacturing, defense, automotive, or industrial ...

X by 2

Technical Lead (Applied AI)

Detroit, MI

Agentic SQL retrieval, MCP integration, agentic tool use, as well as vector databases & RAG techniques implementing retrieval-augmented generation patterns using vector stores (e.g., Pinecone ...

Torc Robotics

Senior, ML Engineer - Auto Tagger

Ann Arbor, MI · On-site

$102K - $140K/yr

Experience building semantic retrieval systems or vector databases for automotive data. Perks of Being a Torc'r Torc cares about our team members and we strive to provide benefits and resources to ...

Torc Robotics

Senior, ML Engineer - Auto Tagger

Ann Arbor, MI · On-site +1

$102K - $140K/yr

Experience building semantic retrieval systems or vector databases for automotive data. Perks of Being a Torc'r Torc cares about our team members and we strive to provide benefits and resources to ...

Stellantis

Agentic AI Developer - Supply Chain

Auburn Hills, MI · On-site

$47.50 - $63.25/hr

... vector databases, or memory architecture • Familiarity with observability, evaluation frameworks, and safety guardrails • Experience integrating agents with ERP, WMS, TMS, or supply chain APIs ...

Waltonen

AI Programmer

Warren, MI · On-site

Familiarity with Retrieval-Augmented Generation (RAG), Vector databases, Cloud platforms, Docker/containerized environments * Experience in manufacturing, defense, automotive, or industrial ...

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Showing results 1-20

All JobsVector Databases JobsVector Databases Jobs in Detroit, MI

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 are popular job titles related to Vector Databases jobs in Detroit, MI? For Vector Databases jobs in Detroit, MI, the most frequently searched job titles are:
What job categories do people searching Vector Databases jobs in Detroit, MI look for? The top searched job categories for Vector Databases jobs in Detroit, MI are:
What cities near Detroit, MI are hiring for Vector Databases jobs? Cities near Detroit, MI with the most Vector Databases job openings:
Vector Databases jobs near you
Full-Stack Data Engineer

Full-Stack Data Engineer

MOTOR Information Systems

Troy, MI • On-site

Full-time

Posted 14 days ago

Job description


FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS
MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who possesses a strong passion for designing, optimizing, refactoring, and upgrading complex data solutions! MOTOR's primary product is Automotive Content, and we need someone who can help us support our Insights-based product suite.
We are looking for someone who wants to be part of our mission to transform the future. We have a rare opportunity for you to use your talent, passion, and expertise to help drive this massive change in how we build our user experience across our product lines, and how consumers experience the MOTOR Product Platform.
This position offers excellent career growth and promotional opportunities, stellar compensation, and the ability to work with the world's premier provider of aftermarket automotive data. Hearst/MOTOR Information Systems will be the best and last place you'll ever work!
Required Experience (Must Have)
  • Expert Python Developer
  • Strong SQL Developer
  • Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift)
  • Strong Experience with Semi-Structured Data (XML, CSV, JSON, Parquet)
  • Strong Automation Experience
  • Experience with Databricks (Delta Lake, Notebooks, SQL Analytics)
  • Experience with Kubernetes (Cluster Orchestration, Container Networking, Pod Management)
  • Experience with DevOps, CI/CD, Deployment Orchestration (Octopus Deploy)
  • Experience with Git and Azure DevOps
  • Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks)
  • Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray)

Helpful Experience (Nice to Have)
  • Experience with LLMs, Machine Learning & Deep Learning Libraries, AI Application Frameworks, Vector Databases
  • Experience with Automotive Data / Industry
  • Experience with Agile / Scrum

Primary Responsibilities
  • Analyze large, and complex, data sets
  • Design, develop and coordinate the generation of Data Pipelines
  • Work collaboratively with team to plan and solve complex problems
  • Design for, or optimize existing pipelines, for performance and cost

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