About the Role
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.