Sr AI/ML Engineer (LATAM Remote)

UP.Labs • Guadalajara,

18h • Remote

About The Position

UP.Labs is a venture studio dedicated to building innovative startup companies from the ground up. We partner with leading corporations and entrepreneurs to identify major industry opportunities, validate new venture concepts, and turn early ideas into real products. We’re seeking a Sr. AI/ML Engineer to help build applied AI systems across computer vision, LLM-powered workflows, intelligent automation, and production AI infrastructure. This role is best suited for someone who is comfortable operating in early-stage, ambiguous environments. Many projects will begin with a business problem, rough concept, or operational pain point rather than a fully defined technical specification. You should be able to take a loosely defined problem, determine a practical technical path forward, make sound assumptions where details are missing, and drive toward a working solution. You’ll work on AI-driven applications involving image detection, object recognition, intelligent automation, and LLM-powered workflows. One key product area involves using computer vision models to identify industrial objects, human interactions, defects, and operational patterns in manufacturing environments. You’ll also build LLM-based capabilities using modern orchestration frameworks, retrieval systems, tool-calling patterns, and agentic workflows. The work will often involve incomplete data, evolving requirements, and open-ended technical decisions. This is a highly collaborative role, but not a heavily prescribed one. You’ll be expected to bring technical judgment, ownership, and initiative to ambiguous problems.

Requirements

• 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 Haves

• 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

Responsibilities

• 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 This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed