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Eligibility: Location: Open to candidates from LATIN AMERICAN countries (e.g., Mexico, Uruguay, Colombia, Peru, Argentina, Chile, Brazil, Costa Rica, Puerto Rico, Nicaragua, Dominican Republic, El Salvador, Honduras, Panama).
Full-time, remote position.
4+ years of applied Machine Learning (ML) experience in a commercial setting.
6+ months of experience with Large Language Models (LLMs) and Generative AI (GenAI).
Proficient in English (C1/C2 level).
Requirements: Bachelors degree in Computer Science, Software Engineering, or a related field.
Proficiency in Python programming and advanced experience in NLP techniques and applications.
Expertise in ML frameworks and libraries (e.g., TensorFlow, PyTorch, Keras, scikit-learn).
Strong background in Object-Oriented Programming (OOP) principles and unit test-driven development.
Experience with cloud environments (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
Familiarity with prompt engineering and LLM optimization techniques.
Experience in developing, deploying, and monitoring ML models.
Strong analytical and problem-solving skills with the ability to propose innovative solutions.
Bonus: Experience in areas such as agent development, fine-tuning LLMs, MLOps, or vector databases.
Role Overview : As an AI Engineer, you will work on cutting-edge AI solutions, enhancing AI-enabled products, and contributing to advanced ML systems.
You will serve as a subject matter expert (SME) on client projects and drive the design and implementation of innovative AI systems.
Key Responsibilities: Build and enhance AI-enabled products.
Serve as an ML SME on client projects.
Design and implement ML systems, including selecting datasets and algorithms.
Conduct ML tests, experiments, and fine-tuning using test results.
Train, retrain, and deploy models while ensuring effective monitoring and performance.
Stay up-to-date with emerging technologies and ML best practices to improve methodologies.
Compensation & Benefits: Annual Salary: $48,000$60,000 (confidential).
20 days of PTO and local public holidays off.
Reimbursement for relevant certifications (e.g., AWS).