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Tier-1 brand, Bengaluru metro, and popular senior ML title increase competition despite specialized ML infrastructure requirements.
Role requires deep ML systems and real-time inference expertise, making skills less transferable across industries.
Explicit 8+ years, mandatory ML systems experience, and specific tech stack preferences increase filtering rigor.
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Design and own high-throughput, low-latency machine learning systems serving over 2000 requests per second with sub-100ms SLAs for the TravelAds platform.
Build and improve ML infrastructure including feature stores, pipelines, embedding/vector services, and enable end-to-end automation of ML lifecycle (training to deployment to monitoring) using workflows such as Flyte or Airflow.
Lead technical direction, mentor engineers, implement ML observability, reliability measures, and develop AI/LLM-powered workflows for automated ML operations and dataset creation.
Bachelor’s degree in Computer Science or related technical field or equivalent experience.
8+ years of relevant professional experience, including building and operating production ML or large-scale distributed systems with system design and operational rigor.
Strong software engineering skills in Python plus at least one of Java, Kotlin, or Scala; deep understanding of distributed systems and performance optimization.
Experience leading technical design on large ML projects and collaborating with Product and business stakeholders to measure ML system business impact.
Experienced in real-time ML inference systems at scale with strict SLAs, operating high-throughput services (1000+ RPS).
Proficient in ML infrastructure and automation tools including Spark, Hive, Databricks, Airflow, Flyte, and cloud-native platforms like AWS SageMaker and EKS.
Skilled in driving operational excellence with incident response, ML observability (drift detection, health dashboards), and applying AI/ML techniques such as LLMs and agentic AI in production environments.