Senior Machine Learning Engineer
Portcast
Tanggal: 5 hari yang lalu
Kota: Pekerjaan jarak jauh, Pekerjaan jarak jauh
Jenis kontrak: Penuh waktu
Jarak jauh

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.
What You’ll Do:
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.
What You’ll Do:
- Develop and deploy machine learning models from initial research to production, ensuring scalability and performance in live environments
- Own the end-to-end ML pipeline, including data processing, model development, testing, deployment, and continuous optimization
- Design and implement machine learning algorithms that address key business problems that our product focuses on in visibility, prediction, demand forecasting and freight audit
- Ensure reliable and scalable ML infrastructure, automating deployment and monitoring processes using MLOps best practices
- Perform feature engineering, model tuning, and validation to ensure that models are production-ready and optimized for performance
- Build, test, and deploy real-time prediction models, maintaining version control and performance tracking
- 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)
- Experience 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
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