• You will work with structured and unstructured data, train and evaluate models, and help integrate AI into real applications
• Support development of AI models for classification, recommendation, forecasting, or NLP tasks
• Prepare datasets, perform feature engineering, and run experiments
• Evaluate model performance and help improve accuracy, latency, and robustness
• Assist with deploying models into production environments (APIs, batch jobs, pipelines)

Collaborate with software engineers, data engineers, and product teams

• Strong Python foundation
• Familiarity with ML basics (supervised/unsupervised learning, evaluation metrics)
• Experience with common libraries (NumPy, pandas, scikit-learn)
• Clear communication and curiosity
• Nice to have
• Exposure to deep learning (PyTorch or TensorFlow)
• Understanding of model deployment (FastAPI/Flask, Docker)

Cloud fundamentals (AWS/GCP/Azure) and basic MLOps concepts

Bachelor’s or Master’s degree in CS, Data Science, AI/ML, Statistics, or related field