2 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Build and maintain production ML lifecycle systems from data processing and feature stores through model serving for journey prediction, churn, conversion propensity, and intervention-matching models.
- Develop subscriber lifecycle forecasting workflows and real-time feature pipelines supporting personalized engagement and next-best-action decisioning.
- Design monitoring for technical health and model-quality metrics including accuracy, drift, and intervention lift.
- Create experimentation frameworks for A/B testing predictive algorithms and intervention strategies.
- Build low-latency, high-throughput serving systems with caching for real-time intervention decisions.
- Establish MLOps practices for experiment tracking, model versioning, deployment automation, feature stores, model hosting, drift monitoring, and automated remediation.
- Scale and optimize model training and serving, including solutions for embedding scaling.
- Own code, system design, and project delivery while collaborating with product managers, data scientists, and cross-functional teams.
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 API performance monitoring tools such as Grafana, Prometheus, and Cloudwatch.
- Experience with machine learning libraries including TensorFlow, PyTorch, JAX, or Keras.
- Ability to develop consistent end-to-end ML pipelines across development and production environments.
- Ability to design scalable ML architectures for site traffic and feature complexity.
- Experience with model and data versioning, resource allocation, scaling, logging, fault monitoring, and model-response monitoring.
- Expertise in production MLOps systems including feature stores, model hosting and versioning, data versioning, prediction and drift monitoring, and automated remediation.
- 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.
- Strong problem-solving skills, ability to work in a fast-paced environment, and commitment to continuous learning.
Tech Stack
Categories
Data EngineeringML Engineering
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