Machine Learning Engineer

📋 Description Design, develop, and deploy end-to-end ML and AI pipelines, from problem framing and Build and maintain robust data and ML pipelines for model training, evaluation, and deployment Implement and evolve ML/LLMOps practices: model versioning, production monitoring, reproducibility Develop APIs and microservices to expose ML/AI models to business applications. Analyze large datasets, identify modeling challenges, propose solutions, and iterate quickly. Collaborate closely with Data, Product, and Engineering teams to turn prototypes into scalable 🎯 Requirements 3-5 years of experience developing and deploying ML models in production Master's degree in Computer Science, Applied Mathematics, Data Science, or related field Expertise in Python and ML frameworks (scikit-learn, XGBoost, LightGBM, HuggingFace, DSPy) Practical experience with MLflow, Kubeflow, DVC, or DeepEval Cloud experience (AWS SageMaker, Azure ML, GCP Vertex AI) and containerization with SQL proficiency and strong feature engineering skills 🎁 Benefits Mission-driven work with team culture Dynamic company events and all-hands meetings Training policy with annual learning budget Remote-friendly and flexible work Family Care Policy including parental leave Mental health support through coaching