Job Description: Machine Learning Engineer Location: Buenos Aires, Argentina (Remote work options available) Company: Mechanized AI About Us: Mechanized AI is at the forefront of AI innovation, leveraging advanced technologies to solve complex real-world problems. We are dedicated to creating cutting-edge solutions that drive modernization and efficiency across industries. As a growing team of passionate professionals, we are committed to fostering an environment that encourages creativity, collaboration, and continuous learning. Key Responsibilities: - Evaluate ML/DL/LLM models - Detect and handle model decay & data drift Experience Requirements: - 4+ years in Machine Learning/Deep Learning/Generative AI (Experience in enterprise companies or startups; teaching or academic experience like Masters/PhD does not count) - 1+ year experience with TensorFlow, PyTorch, or Keras - 1+ year experience in deploying models to production and managing/monitoring them - 1+ year with cloud platforms (AWS/GCP/Azure) - 1+ year in MLOps - 1+ year client-facing experience in AI projects - 6+ months experience with Large Language Models (LLMs) and Generative AI Skills & Expertise: - Strong focus on at least one of the following AI specialities: - MLOps - Classic ML (tabular, regression) - Classic DL (Computer Vision, NLP, tabular, regression) - Generative AI - Deep Reinforcement Learning (DRL) - Full-stack ML - Familiarity with Prompt Engineering: Approaches and best practices - Experience with the following tools and techniques is highly desired: - PySpark - Agent development - Fine-tuning LLMs - Retrieval-Augmented Generation (RAG) optimization - Vector Databases - LLM Architecture & techniques for performance - Model quantization - Data privacy and security (e.g., adversarial attacks, red teaming, integrity) #J-18808-Ljbffr