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Vector Databases Jobs in Arkansas (NOW HIRING)

Principal, Data Scientist

Rogers, AR · On-site

$110K - $220K/yr

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

Principal, Data Scientist

Gravette, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Farmington, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Johnson, AR · On-site

$110K - $220K/yr

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

Principal, Data Scientist

Springdale, AR · On-site

$110K - $220K/yr

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

Principal, Data Scientist

Pea Ridge, AR · On-site

$110K - $220K/yr

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

Principal, Data Scientist

Goshen, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Elm Springs, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Greenland, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Decatur, AR · On-site

$110K - $220K/yr

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

Principal, Data Scientist

Elm Springs, AR · On-site

$110K - $220K/yr

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

Principal, Data Scientist

Bentonville, AR · On-site

$110K - $220K/yr

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

Principal, Data Scientist

Tontitown, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Goshen, AR · On-site

$110K - $220K/yr

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

Principal, Data Scientist

Centerton, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Elkins, AR · On-site

$110K - $220K/yr

Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems. * Architect enterprise-grade AI solutions ...

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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.
What are popular job titles related to Vector Databases jobs in Arkansas? For Vector Databases jobs in Arkansas, the most frequently searched job titles are:
What cities in Arkansas are hiring for Vector Databases jobs? Cities in Arkansas with the most Vector Databases job openings:
Principal, Data Scientist

Principal, Data Scientist

Walmart

Rogers, AR • On-site

$110K - $220K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago


Walmart rating

6.0

Company rating: 6.0 out of 10

Based on 21,840 frontline employees who took The Breakroom Quiz

22nd of 39 rated national retailers


Job description

Position Summary...What you'll do...It’s an exciting time to join Walmart's journey toward building intelligent, AI-powered platforms that transform how we identify risk, improve supplier experience, and drive data-driven decision making at enterprise scale. The Finance Retail & Audit Analytics (FRAA) organization is investing heavily in next-generation AI, Machine Learning, and Data Science capabilities that enable anomaly detection, predictive insights, intelligent automation, and scalable audit intelligence solutions. About Team: The FRAA team is responsible for building intelligent analytics products that help identify risk signals, reduce supplier friction, automate audit processes, and provide predictive decision support across Walmart's global ecosystem. Our vision is to create an enterprise-grade AI platform that combines machine learning, advanced analytics, GenAI, and scalable data engineering to proactively surface insights and drive measurable business outcomes. As a Principal / Staff Data Scientist, you will play a critical role in shaping the technical vision, architecture, and delivery of AI-powered products that support the future of FRAA. You will work closely with engineering, product, analytics, audit, and business teams to operationalize machine learning solutions at scale and drive the adoption of AI-first decision-making across the organization. What you'll do:
  • Lead the AI/ML strategy and technical direction for next-generation FRAA platforms focused on anomaly detection, predictive analytics, supplier intelligence, and audit automation.
  • Design, develop, and deploy scalable machine learning models and AI solutions that solve complex business and risk management challenges.
  • Build and operationalize advanced analytics capabilities including classification, regression, clustering, anomaly detection, forecasting, and recommendation systems.
  • Develop intelligent anomaly detection frameworks leveraging techniques such as Isolation Forest, Random Forest, statistical methods, and unsupervised learning algorithms.
  • Partner with business stakeholders to translate audit, compliance, supplier, and operational challenges into measurable AI/ML solutions.
  • Build end-to-end machine learning pipelines including feature engineering, model training, experimentation, validation, deployment, monitoring, retraining, and optimization.
  • Develop scalable predictive models that proactively identify risks, exceptions, opportunities, and emerging business trends across large enterprise datasets.
  • Leverage semantic search, vector databases, embeddings, NLP, LLMs, and Generative AI technologies to build intelligent audit and decision-support systems.
  • Architect enterprise-grade AI solutions using cloud-native technologies, APIs, microservices, Docker, Kubernetes, and CI/CD deployment frameworks.
  • Collaborate with data engineering teams to design scalable data architectures, feature stores, and ML-ready data products.
  • Work with large-scale distributed data processing frameworks including Spark, BigQuery, DBT, and cloud-native analytical platforms.
  • Establish machine learning governance, model monitoring, explainability, and responsible AI best practices.
  • Drive technical innovation through research, experimentation, and evaluation of emerging AI and machine learning technologies.
  • Mentor and develop data scientists, machine learning engineers, and analytics teams while fostering a culture of innovation and technical excellence.
  • Influence organizational AI strategy, roadmap development, and platform adoption through strong cross-functional leadership and executive communication.
  • Ensure business needs are being met by evaluating the effectiveness of AI solutions, measuring business impact, and continuously improving model performance and operational efficiency.
  • Promote and support company policies, procedures, mission, values, and standards of ethics and integrity while driving responsible and scalable AI adoption.
What you'll bring:
  • Advanced experience designing, building, and deploying machine learning solutions in production environments at enterprise scale.
  • Strong expertise in Python and modern machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, XGBoost, or similar technologies.
  • Deep experience developing machine learning models including:
    • Random Forest
    • Isolation Forest
    • Classification Models
    • Regression Models
    • Clustering Algorithms
    • Anomaly Detection Frameworks
    • Predictive Analytics and Forecasting Models
  • Proven track record operationalizing AI/ML solutions from experimentation through production deployment and monitoring.
  • Strong understanding of feature engineering, model evaluation, model explainability, and MLOps best practices.
  • Experience building scalable ML pipelines and workflows using orchestration frameworks such as Airflow, Kubeflow, MLFlow, or similar platforms.
  • Strong data engineering foundations including SQL, data modeling, ETL/ELT design, and distributed data processing.
  • Experience working with BigQuery, Spark, DBT, Databricks, or comparable cloud-scale analytical platforms.
  • Experience with cloud-native architectures and services across Azure, Google Cloud Platform (GCP), AWS, or hybrid cloud environments.
  • Hands-on experience developing and deploying microservices, REST APIs, containerized applications, and Kubernetes-based solutions.
  • Experience with CI/CD practices and software engineering principles for scalable AI platform development.
  • Strong knowledge of NLP, semantic search, vector embeddings, Retrieval-Augmented Generation (RAG), LLMs, and Generative AI applications.
  • Experience building intelligent systems leveraging embeddings, vector databases, and modern AI agent frameworks is highly preferred.
  • Demonstrated ability to lead technical strategy while influencing cross-functional stakeholders across engineering, product, analytics, and business organizations.
  • Exceptional problem-solving, analytical thinking, and communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.
  • Proven ability to mentor teams, establish technical standards, and drive adoption of AI/ML best practices across large organizations.
  • Passion for innovation and building the future of intelligent audit, analytics, and decision-support platforms.
Preferred Qualifications:
  • PhD or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, Applied Mathematics, or a related quantitative discipline.
  • Experience building enterprise AI platforms supporting audit, compliance, finance, risk management, or operational analytics.
  • Experience implementing GenAI, Agentic AI, RAG architectures, and intelligent automation solutions in production environments.
  • Experience leading large-scale AI transformation initiatives and influencing executive-level technology strategy.
  • Publications, patents, open-source contributions, or demonstrated thought leadership in AI/ML disciplines.
Our Ideal Candidate: We are looking for a technical leader who combines:
  • Deep AI/ML expertise and hands-on model development experience.
  • Strong data engineering and platform architecture foundations.
  • Product mindset with the ability to connect technology investments to business outcomes.
  • Experience operationalizing AI solutions into scalable enterprise platforms.
  • Strategic thinking combined with execution excellence.
  • Passion for building the future of intelligent audit, analytics, and decision-support systems within FRAA.
This role offers the opportunity to shape Walmart's next generation of AI-powered risk, audit, and analytics capabilities while creating measurable impact across one of the world's largest and most complex retail ecosystems. At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable. For information about PTO, see https://one.walmart.com/notices. Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
For information about benefits and eligibility, see One.Walmart.
Bentonville, Arkansas US-30099: The annual salary range for this position is $110,000.00 - $220,000.00
Sunnyvale, California US-11789: The annual salary range for this position is $143,000.00 - $286,000.00
Herndon, Virginia US-10710: The annual salary range for this position is $132,000.00 - $264,000.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
- Stock

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Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related fieldPreferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture.Primary Location...2914 Se I St, Bentonville, AR 72712-3148, United States of AmericaWalmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.

What Walmart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Walmart logo

About Walmart

Sourced by ZipRecruiter

From our humble beginnings as a small discount retailer in Rogers, Ark., Walmart has opened thousands of stores in the U.S. and expanded internationally. Through innovation, we're creating a seamless experience to let customers shop anytime and anywhere online and in stores. We are creating opportunities and bringing value to customers and communities around the globe. Walmart operates approximately 10,500 stores and clubs in 19 countries and eCommerce websites. We employ 2.1 million associates around the world — nearly 1.6 million in the U.S. alone.

Industry

Retail and transportation and warehousing

Company size

10,000+ Employees

Headquarters location

Bentonville, AR, US

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