Machine Learning Engineer

Title : ML Engineer

Location:
Dearborn Michigan

• Design, build, and deploy machine learning models that learn dealership data transmission patterns
• Develop models to detect:
• Missing or delayed data feeds
• Unexpected drops or spikes in transaction volumes
• Deviations from historical trends (e.g., expected vs actual counts)
• Leverage cloud-native ML tooling, prioritizing off-the-shelf and managed services (not building models from scratch)
• Partner with product managers and business stakeholders to:
• understand problem statements
• translate business concerns into ML solutions
• define success metrics
• Implement ML workflows using:
• Python
• SQL / Big Query
• cloud-based data and ML services
• Collaborate with backend engineers to integrate ML outputs into APIs and platform services
• Monitor model performance and data behavior to distinguish:
• real business signals
• upstream data or calculation issues
• Contribute hands-on while also helping organize and guide ML-related work across the team
• Support junior engineers and help upskill team members where appropriate

• Strongly Preferred
• Hands-on experience with Google Cloud Platform
• Experience using pre-built or managed ML models (vs custom research models)
• Big Query experience
• Experience with anomaly detection, trend analysis, or forecasting use cases
• Prior experience in large enterprise or platform teams

• Nice to Have
• Experience with:
• ML monitoring and model performance tracking
• Time-series data
• Data quality or anomaly detection use cases
• Exposure to dealership, automotive, or transaction-based platforms
• Some exposure to Java-based backend systems
• GCP certification

• Senior-level ML Engineer who can:
• work hands-on
• define ML approaches
• partner with business and engineering teams
• Comfortable working in ambiguity and shaping solutions
• Focused on practical ML that drives business outcomes

Dexian is an Equal Opportunity Employer that recruits and hires qualified candidates without regard to race, religion, sex, sexual orientation, gender identity, age, national origin, ancestry, citizenship, disability, or veteran status.