UP.Labs is looking for a Machine Learning Engineer to design, develop, and deploy advanced machine learning and generative AI solutions that drive innovation across our venture portfolio. This hands-on role spans the full ML lifecycle—from data pipeline architecture and model development to production deployment and optimization on cloud platforms.
What You'll Do
- 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.
What We're Looking For
- 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 Have
- 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.
Technical Stack
- Python
- PostgreSQL
- Databricks
- Google Cloud Platform (GCP)
- Amazon Web Services (AWS)
- Microsoft Azure
Work Mode
This is a remote position open to candidates globally.
UP.Labs is dedicated to solving complex problems, driving technological advancements, and creating impactful digital products. We thrive on innovation and launching the next wave of successful startups.
