MLOps Engineer

Required Skills: 8+ years of Machine Learning Engineering or applied AI experience. 3+ years in Lead, Principal, or senior technical leadership roles. Strong hands-on Python development for production-grade machine learning solutions. Advanced experience with Databricks, MLflow, and distributed machine learning workloads. Expertise with TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks. Proven experience building and deploying large-scale recommendation engines. Strong experience developing customer personalization and customer intelligence solutions. Experience with customer segmentation, churn prediction, and customer value models. Strong understanding of Customer 360 platforms and unified customer data. Experience using identity graphs to improve customer matching and prediction accuracy. Strong feature engineering, model evaluation, validation, and lifecycle management experience. Experience designing scalable batch and real-time inference architectures. Proven experience deploying, monitoring, and retraining machine learning models in production. Experience partnering with Data Engineering teams to create ML-ready datasets. Strong architecture experience across Data Science, Engineering, and MLOps platforms. Experience leading technical design reviews and establishing enterprise ML standards. Strong mentoring, stakeholder communication, and cross-functional technical leadership skills.

Preferred Skills: Experience with Snowflake and integrated Databricks data environments. Experience building GenAI, LLM-powered, or agentic AI applications. Experience developing domain-specific AI agents and intelligent assistants. Knowledge of MLOps, feature stores, model serving, and automated retraining. Experience with real-time recommendation and streaming personalization platforms.

For applications and inquiries, contact:View email address on us.fitly.work