Location : EST Remote
Key Responsibilities
Machine Learning Strategy & Development
- Lead development of machine learning solutions supporting:
- Recommendation engines
- Customer segmentation
- Churn prediction
- Customer value prediction
- Offer optimization
- Content personalization
- Design, train, evaluate, and deploy predictive models.
- Create reusable ML frameworks and model development standards.
Customer Intelligence & Personalization
- Leverage Customer 360 and Identity Graph capabilities to improve prediction accuracy.
- Develop intelligent customer insights and personalization capabilities.
- Build models that improve customer engagement, retention, and loyalty outcomes.
- Collaborate with business leaders to align machine learning priorities with strategic objectives.
AI & Next-Generation Capabilities
- Support development of domain-specific AI agents.
- Partner with engineering teams on AI-powered business experiences.
- Contribute to LLM-enabled solutions and intelligent assistant initiatives.
- Evaluate emerging AI capabilities and opportunities for enterprise adoption.
Production ML & Scaling
- Work closely with MLOps Engineers to operationalize models.
- Develop scalable real-time inference solutions.
- Build monitoring, model validation, and retraining processes.
- Optimize model performance and reliability in production.
Technical Leadership
- Provide technical leadership across Data Science, Engineering, and MLOps teams.
- Mentor ML Engineers and Data Scientists.
- Lead architecture discussions and model review sessions.
- Establish best practices for enterprise AI delivery.
Required Qualifications
- 8+ years of Machine Learning Engineering or Applied AI experience.
- 3+ years in a Lead, Principal, or Senior Technical Leadership role.
- Proven experience delivering production-grade machine learning systems.
- Strong expertise with:
- Databricks
- MLflow
- Python
- Machine Learning Frameworks (TensorFlow, PyTorch, Scikit-learn)
- Real-time inference architectures
- Experience building:
- Recommendation systems
- Personalization engines
- Predictive analytics solutions
- Customer intelligence platforms
- Deep understanding of feature engineering and ML lifecycle management.
- Experience partnering with Data Engineering teams to design ML-ready datasets.
Preferred Qualifications
- Customer 360 implementation experience.
- Identity Graph experience.
- Hospitality, Gaming, Entertainment, Retail, Loyalty, or Consumer Digital experience.
- Experience with:
- Snowflake
- MLOps practices
- GenAI solutions
- Agentic AI architectures
- LLM-powered applications
- Real-time recommendation platforms
- Experience supporting enterprise AI transformation initiatives.
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