Sr AI/ML Engineer (LATAM Remote)

Overview

What You’ll Work On

What You’ll Do

• Design, train, evaluate, and deploy machine learning models for real-world applications
• Build and improve computer vision pipelines for object detection, classification, and image understanding
• Build LLM-powered features, agentic workflows, retrieval systems, and internal AI tools
• Work with image data, structured data, unstructured documents, embeddings, vector databases, and tool-calling workflows
• Translate ambiguous business and operational problems into practical AI/ML solutions
• Build data pipelines, inference services, evaluation workflows, and production-ready AI systems
• Evaluate model and agent performance, identify failure modes, and improve reliability over time
• Collaborate with product, engineering, venture, and stakeholder teams to validate concepts and ship working products
• Operate with autonomy in a fast-moving venture environment where priorities, requirements, and available data may evolve quickly

What We’re Looking For

• Strong Python engineering skills and experience building production-oriented AI/ML systems
• Hands-on experience with machine learning fundamentals, model evaluation, training workflows, and data processing pipelines
• Experience building or deploying computer vision systems such as image detection, classification, object recognition, or related workflows
• Experience working with modern LLMs, Generative AI tools, and AI-assisted development workflows
• Hands-on experience building agentic AI workflows, multi-step LLM systems, tool-calling systems, or AI automation workflows
• Experience building RAG, retrieval, or knowledge systems using embeddings, vector databases, document stores, structured data, or graph-based approaches
• Experience deploying AI/ML systems into production environments, including inference services, monitoring, evaluation, and deployment workflows
• Experience with cloud environments such as AWS, Azure, or GCP
• Strong ownership mindset with the ability to operate without fully defined requirements, proactively identify next steps, and communicate tradeoffs clearly
• Strong communication skills and ability to collaborate across technical and non-technical teams

Nice to Have

• Experience with industrial, manufacturing, robotics, logistics, or operational data environments
• Familiarity with edge deployment, camera systems, IoT data, sensor data, or real-time inference workflows
• Experience with tools such as LangGraph, PydanticAI, LangChain, LlamaIndex, ChromaDB, Pinecone, Weaviate, FAISS, pgvector, Neo4j, or similar
• Experience working in startups, venture studios, or early-stage product environments
• Experience building AI-powered internal tools, developer workflows, or automation systems beyond core product work

UP.Labs Summary