
Software Engineer - Machine Learning, Trust and Safety
Job Description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Software Engineer - Machine Learning, Trust and Safety in India.
This role sits at the intersection of machine learning, large-scale systems engineering, and platform trust, focusing on building intelligent solutions that make online marketplaces safer, more reliable, and more user-friendly. You will work on production-grade ML systems that power fraud detection, content moderation, and risk prevention across a global platform. The environment is highly collaborative and fast-moving, bringing together engineers, product teams, and data stakeholders to solve complex, real-world problems at scale. You will contribute across the full ML lifecycle, from experimentation and model development to deployment and optimization in production. The role emphasizes ownership, innovation, and continuous improvement in a cloud-native, Kubernetes-driven infrastructure. It is ideal for engineers who enjoy solving ambiguous problems and applying ML to high-impact trust and safety challenges.
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Software Engineer - Machine Learning, Trust and Safety in India.
This role sits at the intersection of machine learning, large-scale systems engineering, and platform trust, focusing on building intelligent solutions that make online marketplaces safer, more reliable, and more user-friendly. You will work on production-grade ML systems that power fraud detection, content moderation, and risk prevention across a global platform. The environment is highly collaborative and fast-moving, bringing together engineers, product teams, and data stakeholders to solve complex, real-world problems at scale. You will contribute across the full ML lifecycle, from experimentation and model development to deployment and optimization in production. The role emphasizes ownership, innovation, and continuous improvement in a cloud-native, Kubernetes-driven infrastructure. It is ideal for engineers who enjoy solving ambiguous problems and applying ML to high-impact trust and safety challenges.