About the role
AI summarisedSenior Principal Machine Learning Engineer at a technology/ecommerce company, leading the development of ML models and systems for fulfilment optimization. Responsible for designing and deploying scalable ML solutions to improve delivery speed, cost, and customer experience.
BusinessFull-timeData Science
Key Responsibilities
- Design and build large-scale machine learning systems to optimize fulfilment operations, including inventory placement, order routing, and delivery scheduling.
- Lead the development of deep learning and reinforcement learning models to improve prediction accuracy and decision-making in real-time.
- Collaborate with product managers, software engineers, and operations teams to define ML roadmap and translate business requirements into technical solutions.
- Mentor and guide junior and senior engineers, fostering a culture of technical excellence and innovation.
- Drive experimentation and A/B testing frameworks to measure impact of ML models on key business metrics.
- Architect and implement scalable data pipelines and feature engineering infrastructure to support model training and inference.
- Stay abreast of latest research in ML and AI, and apply relevant advancements to fulfilment challenges.
- Present technical findings and strategic recommendations to senior leadership and cross-functional stakeholders.
Requirements
- 10+ years of experience in machine learning, with at least 5 years in a senior or principal role.
- Deep expertise in deep learning, reinforcement learning, and optimization techniques.
- Proficiency in Python and ML frameworks such as TensorFlow or PyTorch.
- Experience with cloud platforms (AWS, GCP, or Azure) and large-scale distributed systems.
- Strong understanding of experimental design and A/B testing methodologies.
- Excellent communication and stakeholder management skills, with ability to influence technical direction.
- Proven track record of delivering production ML systems that drive measurable business impact.
- Experience in supply chain, logistics, or fulfilment domains is a plus.
- PhD or Master's degree in Computer Science, Machine Learning, or a related quantitative field.
- Ability to work in a fast-paced, ambiguous environment and lead cross-functional initiatives.