About the position 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 professional to join our growing team and contribute to our mission of launching the next wave of successful startups. As a Machine Learning Engineer at UP.Labs, You will design, develop, and deploy advanced machine learning and generative AI solutions that drive innovation across our venture portfolio. Your work will span the full ML lifecycle—from data pipeline architecture and model development to production deployment and optimization on cloud platforms. This is a hands-on role requiring strong technical expertise, creativity, and a passion for innovation in the transportation industry. We build high-growth technology startups that enable faster, cleaner, and safer movement of people and goods. Our vision is to transform the moving world by pairing leading corporations and entrepreneurs with a proven methodology for launching and scaling software and hardware companies. We work with corporate investors over a multi-year period to launch a portfolio of mobility-focused ventures. Our team is dedicated to the first year of a new venture’s life cycle, from ideation to minimum viable product build (and beyond)to recruiting and hiring the full-time team who will scale the business.

Responsibilities

• Lead the development and deployment of computer vision solutions (image

classification, object detection, segmentation, OCR) alongside scalable machine learning systems including predictive models, recommendation systems, and advanced analytics pipelines.

• Design and build scalable backend systems and APIs that serve ML models and

integrate with data infrastructure.

• Collaborate with data scientists, software engineers, and business

stakeholders to identify opportunities for machine learning applications.

• Implement end-to-end ML workflows, including data preparation, model

training, evaluation, and deployment.

• Develop and maintain production-grade ML systems, ensuring reliability and

accuracy over time.

• Conduct thorough model testing, validation, and monitoring to ensure accuracy

and stability.

• Stay current with the latest advancements in machine learning, artificial

intelligence, and cloud technologies.

Requirements

• Strong experience in computer vision, including image classification, object

detection, segmentation, OCR, and deploying vision-based models into production environments.

• Strong proficiency in machine learning systems, with extensive experience in

scalable model deployment, feature engineering, and ML operations.

• Solid backend development skills with the ability to build robust, scalable

systems that support ML workloads.

• Advanced Python programming skills for machine learning, data processing, and

backend development.

• Deep expertise in Generative AI technologies, including LLMs, prompt

engineering, and AI application development.

• Strong experience with PostgreSQL for data storage, querying, and database

optimization.

• Proficiency with Databricks for big data processing, collaborative ML

development, and pipeline orchestration. Nice-to-haves

• Working knowledge of Google Cloud Platform (GCP) for deploying and managing

ML infrastructure.

• Familiarity with Amazon Web Services (AWS) for cloud-based ML solutions.
• Experience with Microsoft Azure for enterprise-scale ML deployments.