AI/ML Engineer — Data Products & RAG

Apex Systems; Dearborn (MI); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

401K with company match

Employee Stock Purchase Program (ESPP)

Health Savings Account (HSA)

Employee Assistance Program (EAP)

Certification discounts

Job summary

Everforth Apex is seeking an AI/ML Engineer to build production-ready data products and intelligent workflows across data platforms and cloud engineering. The role spans architecture, implementation, and operations, delivering actionable insights while ensuring data quality, scalability, and reliability.

The candidate will work on Retrieval-Augmented Generation systems, embeddings, and multi-modal inference, with emphasis on secure, observable deployments and end-to-end ownership in a hybrid

Qualifications

• 5+ years of experience building and operating production software, data, or machine learning systems.
• Strong proficiency in Python and SQL.
• Experience with cloud platforms, managed data services, object storage, containers, and distributed computing workloads.
• Experience designing and operating scalable data pipelines and distributed processing systems.
• Hands-on experience applying Large Language Models (LLMs) in production environments, including: prompt engineering, structured outputs, tool integration, model evaluation, production monitoring.
• Deep understanding of: embeddings, vector databases and retrieval, RAG architectures, LLM limitations and mitigation techniques, answer quality and faithfulness optimization.
• Experience with software engineering best practices, including: testing, code reviews, version control, CI/CD, observability, secure development.
• Proven ability to troubleshoot complex production issues through experimentation, profiling, and root-cause analysis.
• Experience with workflow orchestration, batch processing, and job scheduling frameworks.

Responsibilities

• Architect, build, and operate reliable data products that ingest and transform data at enterprise scale.
• Develop production-grade Retrieval-Augmented Generation (RAG) systems that combine semantic search, structured data, and grounded responses for engineering use cases.
• Design and implement agentic AI workflows capable of: Decomposing complex questions, Selecting appropriate data sources and tools, Validating results, Returning explainable answers with citations.
• Develop and evaluate embedding models, document understanding solutions, and multimodal inference workflows while balancing quality, scalability, latency, and cost.
• Deliver analytics and decision-support tools that enable engineers, program teams, and leadership to make informed decisions.
• Build scalable data pipelines and processing systems for large, evolving datasets.
• Create resilient orchestration patterns for batch and near real-time workloads.
• Develop restartable and checkpoint-enabled processing architectures that maintain data integrity during long-running or partially failed workloads.
• Establish data quality, lineage, validation, and governance standards.
• Lead cloud architecture initiatives, including containerization, infrastructure-as-code, and CI/CD deployment practices.
• Design secure, repeatable deployment processes across multiple environments.
• Implement observability, alerting, monitoring, and operational runbooks.
• Ensure system reliability through incident investigation, performance tuning, root-cause analysis, and capacity planning.

Skills

Python

SQL

AI/ML

Expert Systems

GCP

API Development & Integration

Software Testing

Data Analysis

Data & Analytics Dashboards

Java

Education

Bachelor's Degree

Tools

Google Cloud Platform

Java

Job description

Everforth Apex is seeking an AI/ML Engineer to build production-ready data products and intelligent workflows across data platforms and cloud engineering. The role spans architecture, implementation, and operations, delivering actionable insights while ensuring data quality, scalability, and reliability.

The candidate will work on Retrieval-Augmented Generation systems, embeddings, and multi-modal inference, with emphasis on secure, observable deployments and end-to-end ownership in a hybrid