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
Skills Required
- Strong Python engineering skills for production-oriented AI ML systems
- Hands-on experience with machine learning fundamentals and workflows
- Experience building or deploying computer vision systems
- Experience working with modern LLMs and Generative AI tools
- Experience deploying AI ML systems into production environments
- Strong ownership mindset and ability to operate without fully defined requirements
What We Do
We work with global corporate partners to identify the most pressing challenges that they, and broader society, face. Inspired by these complex problems, we launch startups built by proven entrepreneurs, product leaders and technologists that use their agility and talent to develop transformative solutions. After these companies have matured and proven market fit, our corporate partners are able to acquire them, reaping strategic value while enriching their culture and core business. We believe this to be the shortest road to a faster, cleaner, safer, and more accessible future.
Why Work With Us
We launch and innovate 6-8 portfolio organizations a year where no day is the same.
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