Sr. ML Engineer – ML & Applied AI
Core
Design, build, and scale production-grade machine learning and AI systems that power data-driven decision making across the enterprise.
Role type
Senior IC machine learning engineer (MLOps & LLMs)
Builds
Scalable ML platforms, production ML pipelines, and high-performance model serving systems
Domain
Retail / Enterprise AI & MLOps
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, XGBoost, scikit-learn, FastAPI, Docker, Kubernetes, GCP/AWS/Azure, Spark, SQL, Git, CI/CD, MLOps
Preferred skills
LLMs, vector databases, RAG, agentic workflows
Technologies
FastAPI, Spark, Databricks, Docker, Kubernetes, GCP, AWS, Azure, Git
Responsibilities
Architect and build scalable, production-grade ML systems from experimentation to deployment; Design and implement end-to-end ML pipelines including data ingestion, feature engineering, training, validation, and inference; Develop and maintain high-performance model serving systems using APIs for real-time and batch inference; Lead the design and implementation of feature stores and reusable feature pipelines; Build and optimize distributed data processing workflows; Implement and enforce MLOps best practices including CI/CD pipelines, automated retraining, model versioning, and experiment tracking; Design and manage model monitoring and observability frameworks to track performance, drift, latency, and system health; Drive strategies for model retraining, drift detection, and continuous improvement.
Seniority
Senior, hands-on IC
