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Vector Databases Jobs in Trenton, MI (NOW HIRING)

... vector databases and orchestration tools like LangChain - Translating complex business problems into software-engineered AI solutions - Deploying on cloud platforms like AWS, GCP, Azure ...

Full Stack Developer

Dearborn, MI · On-site

$61 - $66/hr

AI coding assistants, Prompt engineering, LLM APIs, Retrieval-augmented generation (RAG), Embeddings, Vector databases, Agentic workflows Engineering Practices * Agile, Secure coding, API design ...

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement ... databases. Should have experience in leveraging various GenAI tools to accelerate software ...

OTA Deployment Engineer

Dearborn, MI · On-site

$84K - $190K/yr

... Vector CAN tools, Diagnostic Engineering Tools (DET), In-Vehicle Software (IVS), or Vehicle and Domain Release (VADR) databases to analyze the software levels of the Electronic Modules in the Vehicle ...

Google AI Lead Architect

Detroit, MI

$54.75 - $75/hr

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement ... databases. Should have experience in leveraging various GenAI tools to accelerate software ...

Proven experience creating, managing, and maintaining network communication databases and ARXML files. * Proficiency with Vector tools such as CANoe and related network analysis and simulation tools.

Showing results 41-53

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 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 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 popular job titles related to Vector Databases jobs in Trenton, MI?

For Vector Databases jobs in Trenton, MI, the most frequently searched job titles are:

What cities near Trenton, MI are hiring for Vector Databases jobs?

Cities near Trenton, MI with the most Vector Databases job openings:

Infographic showing various Vector Databases job openings in Trenton, MI as of August 2026, with employment types broken down into 86% Full Time, 6% Part Time, and 8% Contract. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution.

CTIO AI Engineering Manager

Pwc

Detroit, MI

$73K - $244K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 21 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

26th of 72 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

IFS - Information Technology (IT)

Management Level

Manager

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.
Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Analyse and identify the linkages and interactions between the component parts of an entire system.
Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
Develop skills outside your comfort zone, and encourage others to do the same.
Effectively mentor others.
Use the review of work as an opportunity to deepen the expertise of team members.
Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
The Opportunity
As part of the Data and Analytics Engineering team you will manage client relationships and confirm project deliverables meet expectations. As a Manager, you will lead teams and manage client accounts, focusing on strategic planning and mentoring junior staff while upholding remarkable standards of quality and innovation in deliverables.
Responsibilities
- Work with cross-functional teams to incorporate AI into various applications
- Drive initiatives that enhance project outcomes through creative strategies
- Identify and utilize opportunities for advancements in technology
- Inspire and motivate team members to excel in their contributions
- Uphold exceptional standards of quality and innovation in deliverables
- Foster an environment that encourages continuous improvement and learning
What You Must Have
- Bachelor's Degree
- 5 years of experience in AI engineering or related field
What Sets You Apart
- Master's Degree in Computer Engineering, Data Processing/Analytics/Science, Computer Science, Software Engineering, Artificial Intelligence and Robotics preferred
- Designing, training, and deploying machine learning models
- Developing scalable, cloud-native microservices using Docker and Kubernetes
- Building end-to-end AI applications integrated into various platforms
- Managing CI/CD pipelines for AI systems using GitHub Actions
- Implementing vector databases and orchestration tools like LangChain
- Translating complex business problems into software-engineered AI solutions
- Deploying on cloud platforms like AWS, GCP, Azure
- Contributing to open-source projects or AI/ML publication

Travel Requirements

Not Specified

Job Posting End Date

The salary range for this position is: $73,500 - $212,280. For residents of Washington state the salary range for this position is: $73,500 - $244,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

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About pwc

Sourced by ZipRecruiter

We know that the future success of our firm is contingent on equitable experiences for our people. From recruitment to partnership, we’re working hard to give every person an equitable opportunity to grow and to thrive as part of our community of solvers. We understand that establishing and maintaining a fair, equitable and welcoming environment for all people requires building a culture of belonging: a shift from awareness to empathy — while demonstrating inclusive leadership that cultivates trust among our people and our clients. PwC is committed to advancing diversity, equity and inclusion (DEI) through an evidence-based strategy designed to achieve well-defined and meaningful aspirational goals. Our aim is to solve problems for the long term, as that is how we build trust and continue to build on our culture of belonging. At the core of this endeavor are stated goals and a series of linked programs enabling targeted interventions at key moments in our employees’ career trajectories.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

London, London, UK