Senior Machine Learning Engineer

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Portcast

WebsiteLinkedInAll Job Openings

11 - 50 employees

📦 Logistics

💼 Consulting

🚗 Transport

Logistics • Consulting • Transport

Portcast is a technology company providing real-time transportation visibility and predictive insights to enhance supply chain efficiency. Their platform offers advanced solutions such as container tracking, ocean vessel tracking, air cargo tracking, port congestion tracking, and shipping analytics. Portcast facilitates the automation of logistics operations through predictive ETAs, real-time data access, and analytics for logistics service providers, manufacturers, and technology companies, empowering them to optimize their supply chains and reduce costs.

📋 Description

• 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 • Work directly with product and customer-facing teams to turn loosely defined problems into shipped features • Push back on weak briefs, make decisions when specifications are incomplete, and re-scope quickly as priorities shift • Design and implement ML algorithms for visibility, prediction, demand forecasting, and freight audit • Ensure reliable, scalable ML infrastructure using MLOps best practices for deployment and monitoring • Perform feature engineering, model tuning, and validation • Build, test, and deploy real-time prediction models • Maintain version control and performance tracking for models • Own ML systems from research through production, including monitoring, debugging, and ongoing improvement

🎯 Requirements

• Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field • At least 5+ years of consistently building, deploying, and scaling machine learning models in production environments • Hands-on experience productionising LLM-based systems • Experience with AI agents, multi-step workflows, tool/function calling, and grounding models on proprietary data through retrieval and context design is a bonus • Experience with prompt and model-behaviour versioning, prompt management, evaluation harnesses, guardrails, and monitoring output quality, latency, and cost in live systems • 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 • Experience with AWS, GCP, or Azure • Experience with Docker and Kubernetes • Familiarity with real-time data processing, anomaly detection, and time-series forecasting in production • Experience with large datasets and big data technologies such as Spark and Kafka • First-principles thinking and strong problem-solving • Proactive approach to challenges • Ability to take ownership end to end and work autonomously • Excellent communication and ability to convey complex technical concepts clearly • Strong customer-obsessed mindset

🏖️ Benefits

• Globally distributed, remote-first flexibility • Work with a lean, distributed team across Asia and Europe • Trust, accountability, and collaboration • Work with a tech-first team solving hard problems with technology • Real ownership from day one • Opportunity to grow fast in a company of approximately 30 employees • Direct impact on the business and shipped work