Back
Tier-1 brand, Bangalore metro, and mid-level ML role drive high applicant competition.
Role demands specialized ML engineering and MLOps experience, limiting cross-industry portability.
Explicit 4+ years ML requirement plus mandatory cloud, MLOps, and containerization skills increases shortlisting strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and deliver scalable generative AI services for integration across many applications and thousands of tenants in production at scale.
Drive system efficiencies through automation including capacity planning, configuration management, performance tuning, monitoring, and root cause analysis.
Collaborate with Product Managers, Architects, Data Scientists, and Researchers to translate customer requirements into production-ready AI technologies.
Minimum 4+ years of industry experience in ML engineering building AI systems or services.
Experience designing and building distributed microservices on public clouds such as AWS or GCP.
Proficiency with containerized deployment technologies like Kubernetes and Spinnaker.
Experience with distributed systems and data processing frameworks such as Kafka, Spark, Docker, Hadoop.
Operates effectively in building and scaling large distributed AI and microservice systems in cloud environments.
Experienced collaborating cross-functionally with technical and business teams to deliver innovative AI solutions.
Demonstrates ownership and persistence in driving complex engineering projects to production at scale.