Data Science / ML Engineer
Core
Design and implement machine learning solutions using an event-driven architecture to solve complex problems for clients across various industries.
Role type
Machine Learning Engineer
Builds
Production ML models and data-driven solutions
Domain
Technology / Machine Learning / Cloud Platforms
Deliverable
production ML models
Required skills
Python, TensorFlow, PyTorch, ML-Ops (MLflow, KubeFlow), Azure Databricks, Microsoft Fabric, AWS SageMaker, data modeling, large dataset handling
Preferred skills
Event-driven architecture, Kafka, Pub/Sub, deep learning techniques
Responsibilities
Design and set up machine learning solutions with an event-driven approach; train, evaluate, and implement state-of-the-art deep learning models; set up and optimize ML-Ops pipelines for CI/CD, deployment, and monitoring; handle and model data for ML solutions; work with modern data platforms to build scalable ML solutions.
Seniority
Mid-level, hands-on IC