Data Scientist | Remote LATAM Only

• Experience with Large Language Models (LLMs) and generative AI.
• Hands-on knowledge of Retrieval-Augmented Generation (RAG) and prompt engineering.
• Strong background in graph analytics, anomaly detection, and optimization algorithms.
• Understanding of graph databases (Neo4j, ArangoDB) and knowledge graphs.
• Contributions to open-source AI/ML projects or academic research.

Originally posted on Himalayas

• Proficiency in AI/ML frameworks: TensorFlow, PyTorch, Scikit-learn.
• Strong understanding of supervised, unsupervised, and deep learning models.
• Experience in data analysis and visualization (Pandas, NumPy, Matplotlib, Seaborn).
• Hands-on experience with SQL and NoSQL databases for data retrieval and processing.
• Proficiency in Python, R, or Julia for machine learning and data analysis.
• Experience with cloud AI services (AWS SageMaker, Google Vertex AI, Azure ML).
• Strong knowledge of time-series forecasting, NLP, and recommendation systems.
• Experience in A/B testing, experimentation, and model performance evaluation.
• Familiarity with MLOps tools (MLflow, Kubeflow) for model deployment and tracking.