Artificial Intelligence _ Machine Learning Engineer ( Bangalore, Immediate Joiner, 2+ Yrs )

Company Description eShipz is an AI-powered logistics automation platform that centralizes carriers, sales channels, tracking, non-delivery reports (NDR), and returns into a single system. By using automation and AI-driven insights, eShipz optimizes carrier allocation, flags delivery exceptions, and improves predictability for shipments at scale. The platform supports over 100M shipments delivered, working with 350+ brands and 400+ pre-integrated domestic and international carriers, and manages millions of shipments every month. Built for D2C brands, eCommerce sellers, B2B shippers, 3PLs, and manufacturers, eShipz helps reduce manual errors, lower logistics costs, and enhance supply chain efficiency. The company offers one unified dashboard for end-to-end visibility and control, enabling smarter shipping decisions.
Role Description The Artificial Intelligence / Machine Learning Engineer role at eShipz is a full-time, on-site position based in the Greater Bengaluru Area. This role involves designing, developing, and deploying machine learning models that power logistics automation, such as carrier selection, route optimization, exception handling, and return management. The engineer will work closely with cross-functional teams to understand business requirements, convert them into data-driven solutions, and integrate models into production systems. Daily activities include data exploration, feature engineering, model training and evaluation, performance optimization, and monitoring of deployed models in real-world conditions. The role also requires collaboration on improving platform intelligence, experimenting with new algorithms, and contributing to scalable AI/ML architecture and best practices.
Qualifications
Strong foundation in Computer Science and Algorithms, with the ability to design efficient and scalable solutions.
Experience in Statistics and Pattern Recognition to analyze data, identify trends, and build robust predictive models.
Hands-on expertise in Neural Networks and modern machine learning frameworks for building and optimizing AI models.
Proficiency in programming languages commonly used in ML (such as Python) and familiarity with libraries like TensorFlow, PyTorch, or scikit-learn.
Experience working with real-world, large-scale datasets and building end-to-end ML pipelines in production environments.
Knowledge of cloud platforms and MLOps practices for deployment, monitoring, and maintenance of ML models.
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field.
Ability to collaborate in a fast-paced environment, communicate technical concepts clearly, and deliver solutions with quick turnaround (immediate joiners preferred).

Work arrangement
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