AI/ML Engineer
Core
Design, develop, and deploy machine learning models and pipelines for classification, regression, clustering, recommendations, or NLP tasks to power intelligent products.
Role type
AI/ML Engineer
Builds
Production ML models and scalable data pipelines
Domain
Data Science / Machine Learning
Deliverable
production ML models
Required skills
Python, Scikit-learn, TensorFlow, PyTorch, XGBoost, data preprocessing, feature engineering, model evaluation, supervised/unsupervised learning, Git, Jupyter, pandas, NumPy, Matplotlib, Seaborn
Preferred skills
AWS/Azure/GCP, SageMaker/Vertex AI, GenAI prompting, LLM hosting, spaCy, Hugging Face Transformers, NLTK, MLOps (MLflow, DVC, Kubeflow), deep learning, neural networks, REST APIs, Flask, FastAPI, Docker
Responsibilities
Design and deploy ML models for various tasks; clean and preprocess large datasets; develop scalable data pipelines with data engineers; experiment with algorithms to improve performance; monitor and maintain production models including retraining and drift detection; integrate ML models into applications; document processes and experiments; stay current with ML research and trends
Seniority
Mid-level, hands-on IC