Machine Learning Engineer | Supply Chain Agentic AI Systems
DEARBORN, MI (HYBRID)
W2 CONTRACT ONLY
OPEN RATE
OVERVIEW
Responsible for predicting and/ or extracting meaningful trends/ patterns/ recommendations from raw data, leveraging data science methodologies including Machine Learning (ML), predictive modeling, math, statistics, advanced analytics, etc.
You will work on cutting-edge multi-agent AI systems leveraging LLMs (GPT, Gemini, Claude) to generate recommendations, detect anomalies, and improve decision-making across logistics and inventory management.
What You’ll Do
- Design and deploy machine learning models to improve inbound logistics and supply chain efficiency
- Develop agentic AI systems that:
- Monitor transportation ecosystem health
- Generate actionable recommendations for operations
- Support cross-plant inventory optimization
- Build and integrate middleware APIs and data pipelines that aggregate operational data
- Implement predictive, prescriptive, and anomaly detection models
- Collaborate in Agile/Scrum teams (JIRA, standups, sprint work)
- Contribute to team demos and solution showcases
- Deliver production-ready, scalable ML solutions, not just prototypes
- Support knowledge transfer and enablement of AI capabilities within the team
Required Qualifications
- 5+ years of experience in Data Science, Machine Learning, or ML Engineering
- Proven experience building AND deploying models into production
- Strong expertise with:
- Python & Machine Learning frameworks
- Agentic AI / LLM-based systems (or strong GenAI exposure)
- Supply chain, logistics, or operations analytics
- Experience designing end-to-end ML solutions, from data ingestion to deployment
- Ability to translate business needs into data-driven solutions
Preferred Qualifications
- Experience with LLM integration and orchestration (GPT, Claude, Gemini)
- Knowledge of API development / middleware systems
- Automotive or supply chain domain experience
- Familiarity with:
- Data pipelines & data management
- Advanced analytics and optimization techniques
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