Overview:

Technical Challenge:

In this role you will:

• 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.

Required Skills:

• 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.

Preferred Expertise:

• 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.

UP.Labs Summary:

Location: Remote