Analyze manufacturing and quality datasets to find defect trends and root causes
Design and build AI agents that answer quality questions and generate reports
Build dashboards, data models, and automated analytics for quality KPIs
Integrate AI agents with manufacturing databases and quality systems
Validate AI-generated results for accuracy and traceability
From the employer’s posting
Analyze large datasets from manufacturing and quality systems to identify defect trends, correlations, anomalies, and potential root causes.
Design, develop, and implement AI agents that analyze data, answer quality-related questions, generate reports, and support engineering workflows.
Develop and maintain dashboards, data models, and automated analytics solutions to monitor quality performance and manufacturing processes.
Integrate AI agents with manufacturing databases, quality management systems, technical documentation, and other enterprise data sources.
Validate AI-generated results and analytical outputs to ensure accuracy, reliability, traceability, and relevance to manufacturing and quality processes.
Education & alternatives
- Document analytical methods, AI workflows, data integrations, and solution functionality.
QUALIFICATIONS:- Bachelor's degree in Data Science, Computer Science, Information Technology, Engineering, Statistics, or a related technical field.
- Relevant professional experience in data analytics, AI development, software engineering, or manufacturing quality may be considered in place of a degree.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
SQL
Azure
Power BI
Where the posting names them
- Experience translating business or engineering requirements into technical solutions.
REQUIRED SKILLS:- Proficiency in Python and SQL for data processing, analysis, and automation.
- Experience with data analytics, statistical analysis, and data visualization.
- Strong collaboration skills and the ability to work with cross-functional technical and operational teams.
PREFERRED SKILLS:- Experience with Microsoft Fabric, Azure AI, Microsoft Copilot Studio, or similar data and AI platforms.
- Knowledge of retrieval-augmented generation (RAG), AI tool integration, and enterprise AI architectures.
- Experience with data analytics, statistical analysis, and data visualization.
- Ability to develop dashboards, reports, and analytical solutions using Power BI or comparable tools.
- Knowledge of AI agents, agentic AI concepts, large language models (LLMs), and prompt engineering.
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
SWJ Technologie specializes in providing engineering, planning, and project management services across various industries. We are currently seeking a Quality Data & AI Agent Engineer for a client in the automotive industry, specializing in car manufacturing. This role is a contractor position based in Vance,ALthat requires onsite presence. If you’re eager to grow your career and make a meaningful impact on exciting projects, we look forward to your application.
PURPOSE: The Quality Data & AI Agent Engineer analyzes manufacturing and quality data to identify trends, detect anomalies, investigate root causes, and drive continuous improvement. The role develops AI agents, automated analytics, and digital workflows that transform complex data into actionable insights, improve quality performance, and support data-driven engineering decisions.
RESPONSIBILITIES:
Analyze large datasets from manufacturing and quality systems to identify defect trends, correlations, anomalies, and potential root causes.
Develop and maintain dashboards, data models, and automated analytics solutions to monitor quality performance and manufacturing processes.
Design, develop, and implement AI agents that analyze data, answer quality-related questions, generate reports, and support engineering workflows.
Integrate AI agents with manufacturing databases, quality management systems, technical documentation, and other enterprise data sources.
Develop and automate workflows for quality KPI monitoring, defect and failure analysis, root-cause investigation, reporting, and early-warning detection.
Apply statistical methods and machine learning techniques to identify patterns, predict potential quality issues, and uncover improvement opportunities.
Collaborate with Quality, Production, Engineering, IT, and Data/AI teams to translate operational requirements into scalable digital solutions.
Validate AI-generated results and analytical outputs to ensure accuracy, reliability, traceability, and relevance to manufacturing and quality processes.
Support the implementation of data-driven problem-solving methods and continuous improvement initiatives.
Develop reusable analytics components, AI agents, and automated workflows that can be scaled across production areas and quality applications.
Document analytical methods, AI workflows, data integrations, and solution functionality.
QUALIFICATIONS:
Bachelor's degree in Data Science, Computer Science, Information Technology, Engineering, Statistics, or a related technical field.
Relevant professional experience in data analytics, AI development, software engineering, or manufacturing quality may be considered in place of a degree.
Experience working with complex datasets and developing data-driven solutions.
Understanding of manufacturing processes, quality management, and industrial data environments.
Experience translating business or engineering requirements into technical solutions.
REQUIRED SKILLS:
Proficiency in Python and SQL for data processing, analysis, and automation.
Experience with data analytics, statistical analysis, and data visualization.
Ability to develop dashboards, reports, and analytical solutions using Power BI or comparable tools.
Knowledge of AI agents, agentic AI concepts, large language models (LLMs), and prompt engineering.
Experience integrating data sources, APIs, and software tools to support automated workflows.
Strong analytical and problem-solving skills, including the ability to identify patterns, investigate anomalies, and evaluate potential root causes.
Ability to interpret complex data and communicate findings in a clear, actionable manner.
Attention to data quality, analytical accuracy, and the validation of AI-generated results.
Strong collaboration skills and the ability to work with cross-functional technical and operational teams.
PREFERRED SKILLS:
Experience with Microsoft Fabric, Azure AI, Microsoft Copilot Studio, or similar data and AI platforms.
Knowledge of retrieval-augmented generation (RAG), AI tool integration, and enterprise AI architectures.
Experience developing AI-powered applications, autonomous agents, or multi-step automated workflows.
Knowledge of machine learning techniques, anomaly detection, and predictive analytics.
Experience with manufacturing execution systems (MES), quality management systems (QMS), enterprise resource planning (ERP) systems, or industrial databases.
Familiarity with Root Cause Analysis (RCA), Pareto analysis, Statistical Process Control (SPC), process capability, and quality KPIs.
Understanding of defect and failure analysis, manufacturing process optimization, and continuous improvement methodologies.
Experience automating engineering reports, quality investigations, and operational decision-support processes.
Knowledge of data governance, model validation, AI reliability, and traceability requirements
PHYSICAL REQUIREMENTS:
Work is normally performed in an office, laboratory, manufacturing floor, or machine shop setting where physical work includes, but is not limited to sitting, standing, reaching, kneeling, bending, and lifting up to 25 lbs.
Must be able to understand and comply with all relevant safety practices.
FLSA STATUS/WORKING SCHEDULE:
Location: Vance,AL
Schedule: Full Time
AssignmentStart: asap
DISCLAIMER: This job description is a high-level overview of general expectations of this position. It is not intended to list every responsibility of the position, nor does it represent an employment contract of any kind.
SWJ TECHNOLOGY and all of its subsidiaries (i.e., SWJ MACHINING and ProjectOne US) are Equal Opportunity Employers and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender, disability status, protected veteran status, or any other characteristic protected by law.