Machine Learning Engineer
Core
Developing, deploying, and optimizing machine learning models (NLP, predictive analytics, automation) to power an AI-driven insurance platform.
Role type
Machine Learning Engineer
Builds
Scalable ML pipelines, production-ready models, and APIs for real-time insurance applications
Domain
Insurance / Fintech / Machine Learning
Deliverable
production ML models
Required skills
Python, TensorFlow/Pytorch/Scikit-Learn, MLOps (MLflow/Docker/Kubernetes/SageMaker), Cloud platforms (AWS/GCP/Azure), Spark/Dask/Ray, NLP, time-series forecasting, recommendation systems
Preferred skills
RAG, LLMs, Generative AI, Kafka, insurance/fintech domain knowledge
Technologies
TensorFlow, PyTorch, Scikit-Learn, MLflow, Docker, Kubernetes, SageMaker, AWS, GCP, Azure, Spark, Dask, Ray, Kafka, Git
Responsibilities
Design, develop, and deploy ML models; Build and optimize scalable ML pipelines; Implement, fine-tune, and monitor models in production; Translate research models into production-ready solutions; Develop and maintain APIs for model integration; Optimize model performance and scalability; Maintain best practices in ML engineering (version control, CI/CD, cloud deployment)
Seniority
Mid-level (3-5 years experience)