Senior Machine Learning Engineer

About the Company

This position represents Portcast, a venture-backed startup supported by SGInnovate, based in Singapore. Portcast develops a cutting-edge real-time transportation visibility platform aimed at enhancing global supply chain operations. The company empowers shippers, manufacturers, and logistics providers by transforming data into actionable insights that minimize costs, streamline exception management, and accelerate invoice processing. Founded in 2018, Portcast combines software engineering, data science, and logistics expertise to drive digital transformation in the industry.

Job Overview

We are seeking a seasoned Senior Machine Learning Engineer capable of managing the entire machine learning lifecycle—from research and development through deployment and scaling in real-world applications. The successful candidate will design robust algorithms addressing key business challenges such as visibility, prediction, demand forecasting, and freight auditing. This role requires a highly independent individual who thrives in an environment with minimal team support and extensive ownership.

Key Responsibilities

• Lead the development, deployment, and maintenance of machine learning models, ensuring their scalability and operational efficiency in production settings.
• Manage the complete ML pipeline including data preprocessing, model creation, testing, ongoing deployment, and iterative optimization.
• Collaborate directly with product and customer-facing teams to translate loosely defined problem statements into deliverable features, adjusting scope dynamically as priorities evolve.
• Design and implement machine learning algorithms aligned with the company’s core product focus areas: visibility, predictive analytics, demand forecasting, and freight auditing.
• Establish reliable, scalable ML infrastructure applying MLOps best practices for automation of deployment and monitoring.
• Conduct feature engineering, hyperparameter tuning, model validation, and performance enhancement to prepare models for production.
• Develop and manage real-time prediction models, maintaining version control and tracking performance metrics.

Qualifications and Experience

• A Bachelor’s, Master’s, or PhD degree in Computer Science, Engineering, or related fields.
• Minimum of 5 years’ experience developing, deploying, and scaling machine learning models in production environments.
• Hands-on expertise with deploying large language model (LLM) systems in production, including AI agents, multi-step workflows, tool/function invocation, and model grounding using proprietary data. Experience with prompt engineering, version control, evaluation frameworks, guardrails, and monitoring latency, cost, and output quality is highly valued.
• Demonstrated ability to take products from R&D to production in fast-paced startup environments.
• Strong proficiency in Python and SQL, with practical experience in cloud environments (AWS, GCP, or Azure) and container technologies such as Docker and Kubernetes.
• Familiarity with real-time data streams, anomaly detection techniques, and time series forecasting in live systems.
• Experience handling extensive datasets and scalable big data tools like Apache Spark and Kafka.
• Analytical mindset with first-principles problem solving and proactive ownership.
• Excellent verbal and written communication skills, with a customer-centric outlook.

Benefits and Work Culture

• Fully remote with a globally distributed and collaborative team across Asia and Europe that values trust and accountability.
• A technology-driven environment that embraces solving complex challenges through innovation and data science.
• Significant ownership from the outset with direct impact on business results within a small, nimble team.
• Opportunities to advance quickly by making tangible contributions and seeing your work influence company direction.

Core Values

• Curiosity: Deep investigation into data and model behavior beyond surface metrics.
• Ownership: End-to-end responsibility for models from research through production and beyond.
• Raising the Bar: Commitment to production quality, scalability, reliability, and cost efficiency.
• Effectiveness: Emphasis on models that yield real customer and product impact, not just accuracy.

Additional Information

This role is posted for Portcast through SGInnovate. Interested candidates are encouraged to engage directly via the specified recruitment channel.