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UP.Labs is a first-of-its-kind venture lab unlocking the future of transportation and mobility.
The Role
The role involves designing, deploying, and maintaining LLM platforms, developing AI systems, managing pipelines, and providing deployment guidance.
Summary Generated by Built In
Overview
UP.Labs is a dynamic venture studio dedicated to building innovative startup companies from the ground up. Our team thrives on solving complex problems, driving technological advancements, and creating impactful digital products. We’re seeking a highly skilled Dev/LLMOps Eng to join our growing team and contribute to our mission of launching the next wave of successful startups.
Technical Challenge
We're looking for a Dev/LLMOps Eng with a deep technical foundation and a passion for building agentic AI systems that integrate directly with Large Language Models (LLMs). This is an opportunity to drive the development of intelligent, autonomous agents that reason, plan, and interact with users in real time.
We are looking for an experienced Dev/LLMOps Engineer to design, deploy, and maintain the infrastructure that supports our Large Language Model (LLM) platforms. This role combines DevOps best practices with AI/ML infrastructure expertise, ensuring reliable model training, fine-tuning, and deployment at scale. The ideal candidate is highly skilled in cloud automation, container orchestration, and model-serving pipelines.
Responsabilities:
- Own the strategy and execution of agentic AI systems using LLMs and autonomous decision-making components.
- Develop and scale prototypes into MVPs that demonstrate the real-world viability of complex AI ideas.
- Collaborate cross-functionally with engineers and product managers to embed LLMs and decision agents into user-facing features.
- Build and manage CI/CD pipelines for LLM training and deployment workflows.
- Provide technical guidance on DevOps and deployment strategies for AI models.
Requirements:
- 7+ years of experience deploying and managing diverse machine learning and GenAI solutions in production, with a strong focus on architecture, end-to-end ownership and systems-level thinking.
- Proven experience with LLM integration, LLM-based agents, or related autonomous reasoning systems is required.
- Experience building and deploying end-to-end AI systems: from unstructured data cleansing to model training, evaluation, deployment, and monitoring.
- Databricks experience, familiarity with Langchain and Databricks GenAI capabilities is strongly recommended.
- Cloud Platforms: Experience with AWS, GCP, or Azure for access control, multi-tenant deployments and CI/CD pipelines, DevOps tools, deployment patterns and infrastructure management.
- Ability to move fast and learn fast, strong proficiency with agile, lean product development is a must.
Preferred Expertise:
- Advanced degree (Master’s or PhD) in Machine Learning, Computer Science, or related field.
- Expert-level proficiency with DevOps and MLOps practices and tools for managing data, GenAI and machine learning resources and workflows.
- Fundamental and operational knowledge of designing and operating security and access controls and ability to scale it up from prototype to enterprise.
- Extensive knowledge of the Data Engineering stack, specifically Databricks, is a strong plus.
- Experience in the aviation industry is a bonus.
Top Skills
AWS
Azure
Ci/Cd
Container Orchestration
Databricks
GCP
Llm Integration
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The Company
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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