Related skills
sql python pandas pytorch scikit-learn📋 Description
- Developing end-to-end ML systems for production use.
- Deploy GenAI/agentic AI and ML-Ops in high-stakes environments.
- Forecast work volume, schedule agent shifts, and manage time-off.
- Design and own the full lifecycle of workforce scheduling.
- Build scalable models and integrate into customer contact centers.
- Collaborate across CX-R&D Engineering teams.
🎯 Requirements
- 5+ years as an applied researcher or research engineer.
- ML, GenAI, agentic AI, and ML-Ops experience.
- Proficient in Python, PyTorch, scikit-learn, HuggingFace.
- Time-series forecasting and mathematical optimization (Gurobi).
- Cloud deployment (AWS) and ML pipelines; Docker, SQL, pandas.
- MSc in CS or related field; strong communication and agile.
🎁 Benefits
- NiCE-FLEX hybrid model: 2 days in-office, 3 remote weekly.
- Global team with opportunities across roles and locations.
- Fast-paced, collaborative environment focused on learning.
- Career growth across multiple disciplines and locations.
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