We are searching for a highly skilled AI Engineer with a strong background in Machine Learning (ML) and at least four years of hands-on experience in commercial environments beyond academia. The ideal candidate is passionate about AI, stays updated on the latest advancements, and is eager to contribute to innovative AI-driven solutions.
Location: Open to candidates located anywhere in Mexico, Uruguay, Colombia, Argentina, Chile, Brazil, Costa Rica, Puerto Rico, Nicaragua, Dominican Republic, El Salvador, Honduras OR Panama

REQUIREMENTS

• 4+ years of ML experience at a start-up or larger enterprise — high priority
• 6+ months of experience with Large Language Models (LLMs) and Generative AI (GenAI) applications – high priority
• Client delivery experience — high priority
• Effective written and oral communications skills (C1/C2 — advanced/proficient level English is required) — high priority
• Bachelor’s degree in computer science, software engineering or related field
• Experience with cloud environments (e.g., AWS, Azure, GCP)
• Experience with ML frameworks and libraries (TensorFlow, PyTorch, Keras, scikit-learn)
• Experience developing, deploying, and managing/monitoring models
• Knowledge of containerization technologies (e.g., Docker, Kubernetes) and microservices architecture
• Expertise in Object-Oriented Programming (OOP) principles and unit test-driven development methodologies
• Advanced experience in NLP techniques and applications
• Proficiency in Python programming
• Familiarity with prompt engineering approaches and best practices
• Knowledge of data structures, data modeling, and software architecture
• Analytical and problem-solving skills, with the ability to propose innovative solutions and troubleshoot issues
• Ability to work independently and as part of a collaborative team in a fast-paced environment

Experience in any of the following is preferred, not required:

• Agent development
• Data privacy
• Fine tuning LLMs
• LLM architecture and techniques for performance
• MLOps
• ML evaluation
• Model decay and data drift detection and handling
• Pulumi, Terraform and/or Cloud SDKs
• PySpark
• Quantization
• Retrieval-augmented generation (RAG) optimization
• Security

• Vector databases

• Contribute to building and enhancing our Mechanized AI platform and AI-enabled products including mAI Modernize
• Serve as ML SME on client projects as needed
• Design ML systems
• Research and implement appropriate ML algorithms and tools
• Select appropriate datasets and data representation methods
• Run ML tests and experiments
• Perform statistical analysis and fine-tuning using test results
• Train and retrain systems when necessary
• Extend existing ML libraries and frameworks
• Stay current with emerging technologies and ML best practices to continuously improve our methodologies and tools.