As a Machine Learning Engineer at UP.Labs, you will design, implement, and optimize machine learning models to solve complex problems in manufacturing, logistics, and supply chain management. You will be responsible for deploying scalable solutions in Cloud environments and integrating these models into production systems. This is a hands-on role requiring strong technical expertise, creativity, and a passion for innovation in the transportation industry.

• Design, build, and deploy machine learning models and pipelines using AWS, Microsoft Azure and/or GCP tools
• Collaborate with data scientists, software engineers, and business stakeholders to identify opportunities for machine learning applications.
• Tune and optimize machine learning models to enhance performance and scalability.
• 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.
• Work with large-scale datasets, utilizing distributed computing tools such as Spark or Databricks.
• 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.

• Bachelor’s degree in Computer Science, Data Science, Mathematics, or a related field.
• 4+ years of experience in building and deploying machine learning models.
• Proficiency with programming languages such as Python, R, and/or Java.
• Expertise in at least one major cloud provider – AWS, Microsoft Azure and/or GCP 
• Strong experience working with Databricks
• Familiarity with cloud provider ML tooling, such Azure ML, Sagemaker, and/or Vertex AI
• Strong understanding of machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Solid knowledge of version control systems (e.g., Git) and CI/CD pipelines for ML systems.
• Strong problem-solving skills and ability to work collaboratively across teams.

• Advanced degree (Master’s or PhD) in Machine Learning, Computer Science, or related field.
• Experience in the transportation and logistics industry.
• Familiarity with IoT data and edge AI applications.
• Knowledge of Big Data tools like Hadoop, Spark, or Kafka.
• Experience with MLOps practices and tools for managing machine learning workflows.