Machine Learning Engineer

• Build scalable data pipelines that ingest and process large volumes of multi-source data, including tracking data, operational events, and IoT sensor streams.
• Design and develop machine learning models for:
• Delay prediction
• Exception and anomaly detection
• Transport plan optimization
• Event and milestone forecasting
• Create continuous learning pipelines that adapt to changing operational patterns.
• Scale ML infrastructure to support near real-time predictions and production workloads.
• Collaborate closely with engineering teams to integrate models into live products using testing and monitoring best practices.
• Help define the long-term machine learning strategy, architecture, and data roadmap.

• 4+ years of experience building and deploying machine learning models in production.
• Strong Python skills with experience using frameworks such as PyTorch, TensorFlow, and scikit-learn.
• Hands-on experience building data pipelines, stream processing, and working with graph databases.
• Experience designing scalable ML infrastructure and production workflows.
• Comfortable working in an environment where you'll help shape the technical direction rather than simply execute predefined tasks.

• Clear path of progression
• Full package
• Competitive salary
• Real ownership
• Close team

If you're interested in building AI solutions that have a tangible impact and want to work on challenging machine learning problems at scale, I'd love to hear from you.