Senior Machine Learning Engineer

October 3

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Portcast

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Supply Chain • Logistics • Software

11 - 50

Description

• About Us: • Portcast is a venture-backed startup which predicts global trade flows to help logistics and shipping companies become more profitable. • We are a predictive analytics company that offers a fast-paced, innovative environment where you will be empowered to sell our AI-product to C-level executives. • We are customer-obsessed and are constantly working to provide our customers access to actionable and insightful data to build resilient supply chains. • Based in Singapore, and backed by leading VCs and senior industry advisors, Portcast is a team of young tech and industry talent building a game-changing product for the logistics and shipping industry. • About the role: • We are looking for a Senior Machine Learning Engineer who specializes in deploying ML and AI models into production. • You will handle the full lifecycle—from research and model building to deployment and scaling in real-world environments. • This hands-on role requires designing robust algorithms that address key business problems, particularly in visibility, prediction, demand forecasting, and freight audit. • Your focus will be on ensuring model accuracy, reliability, and scalability in production systems.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field. • 5+ years of experience in building, deploying, and scaling machine learning models in production environments. • Experience deploying Generative AI models in production environments, with a strong understanding of Retrieval-Augmented Generation (RAG), AI Agents, and expertise in prompt engineering techniques • Proven experience with the full product lifecycle, taking models from R&D to deployment in fast-paced environments. • Experience working in a product-based company, preferably within a startup environment with early-stage technical product development. • Strong expertise in Python and SQL, along with experience in cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). • Familiarity with real-time data processing, anomaly detection, and time-series forecasting in production. • Experience working with large datasets and big data technologies like Spark and Kafka to build scalable solutions. • First-principles thinking and excellent problem-solving skills, with a proactive approach to addressing challenges. • A self-starter mentality, with the ability to take ownership of projects from end to end and work autonomously to drive results. • Excellent communication skills, with the ability to convey complex technical concepts and a strong customer-obsessed mindset.