Own the end-to-end machine learning lifecycle, including code, design, delivery, and production quality.
Build scalable recommendation systems and near-real-time feature pipelines using big data and stream-processing technologies.
Design low-latency caching and storage solutions for real-time recommendations.
Develop scalable ML architectures, production deployment workflows, model hosting, versioning, monitoring, and automated remediation.
Implement API performance monitoring and systems that detect and respond to faults in resources, data streams, and model responses.
Evaluate technologies and influence architecture and design decisions for complex systems.
Collaborate with product managers and cross-functional teams to deliver software aligned with business objectives.
Requirements
Strong coding skills in Python, Java, Golang, or Scala.
Experience with big data frameworks such as Spark and Kubernetes for data and ML workloads.
Proficiency with Grafana, Prometheus, and CloudWatch for API performance monitoring.
Experience building end-to-end machine learning pipelines that maintain consistency between development and production.
Ability to design scalable ML architectures for site traffic and feature complexity.
Familiarity with model and data versioning, resource allocation and scaling, logging, feature stores, model hosting, prediction monitoring, and drift monitoring.
Strong problem-solving skills and ability to work effectively in a fast-paced environment.
B.Tech, B.E., Master's, or equivalent degree.
At least 4+ years of professional experience in software engineering roles and a record of independently delivering high-quality projects.
Benefits
Full-time role based in Bangalore.
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