Senior Machine Learning Engineer

Role Description

We are looking for a Senior Machine Learning Engineer who specializes in taking ML and AI models into production. You will own the full lifecycle, from research and model building to deployment and scaling in real-world environments. This is a hands-on role designing robust algorithms that address our core business problems, particularly in visibility, prediction, demand forecasting, and freight audit. Your focus is ensuring model accuracy, reliability, and scalability in live production systems. You'll be one of two on our data science team, so this role is built for someone highly independent, ambitious, and curious, comfortable owning problems end to end without a big team around them.

What You’ll Own:

• 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: data processing, model development, testing, deployment, and continuous optimization.
• Comfortable building from a rough outline rather than a finished spec. Work directly with product and customer-facing teams to turn loosely defined problems into shipped features, and re-scope quickly when priorities shift.
• Design and implement machine learning algorithms that address the key business problems our product focuses on: visibility, prediction, demand forecasting, and freight audit.
• Ensure reliable, scalable ML infrastructure, automating deployment and monitoring using MLOps best practices.
• Perform feature engineering, model tuning, and validation so models are production-ready and optimized for performance.
• Build, test, and deploy real-time prediction models, maintaining version control and performance tracking.

Qualifications

• Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field.
• At least 5+ years of end-to-end and consistent building, deploying, and scaling machine learning models in production environments.
• Hands-on experience productionising LLM-based systems.
• Bonus points for designing AI agents and multi-step workflows, tool/function calling, and grounding models on proprietary data through retrieval and context design.
• Proven experience across the full product lifecycle, taking models from R&D to deployment in fast-paced environments.
• Experience in a product-based company, preferably a startup with early-stage technical product development.
• Strong expertise in Python and SQL, 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 with large datasets and big data technologies like Spark and Kafka to build scalable solutions.
• First-principles thinking and strong problem-solving, with a proactive approach to challenges.
• A self-starter who takes ownership end to end and works autonomously to drive results.
• Excellent communication, with the ability to convey complex technical concepts clearly and a strong customer-obsessed mindset.

Benefits

• Globally distributed, remote-first flexibility: Work with a lean, distributed team across Asia and Europe, built on trust, accountability, and collaboration.
• Tech-first team: Work with like-minded people who care about solving hard problems with technology.
• Real ownership from day one: Own ML systems end to end, from research to production, and grow fast.
• Impact you can see: Your work moves the business directly, and you'll watch your ideas and decisions ship and matter.

Company Description

Portcast is a venture-backed, Singapore-based logistics technology startup building a real-time transportation visibility platform for global supply chains. We help shippers, manufacturers, and logistics service providers turn data into decisions and decisions into measurable business impact.

Founded in 2018 and backed by leading technology investors, we are building for an industry at a critical inflection point of digital transformation. Our team of software engineers, data scientists, and logistics experts is on a mission to make supply chains not just visible, but decisively actionable, end to end.