Senior AIML Engineer AI Center of Excellence (CoE)
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Job Location:
Monthly Salary:
Posted on:
2 days ago
Vacancies:
1 Vacancy
Job Summary
Senior AI/ML Engineer - AI Center of Excellence (CoE)
Location: Hybrid(Trivandrum/Kochi)
Role: Permanent
Budget: Upto 30LPA
Experience: 8-12 years
Must Have Skills:
8-12 years total including 4-6 years software engineering 4-5 years hands-on AI/ML (overlap acceptable). 2 years technical leadership preferred.
Strong software engineering fundamentals: Python solid backend engineering; ability to integrate with UI layers (web apps) as needed.
Hands-on AI/ML delivery: model development deployment experience across traditional ML and deep learning plus GenAI patterns (RAG prompt engineering evals; fine-tuning is a plus).
Experience building agentic / tool-using LLM systems (or equivalent orchestration patterns) in real implementations.
Cloud proficiency in one: AWS or Azure or GCP (compute storage networking security; managed ML services a plus).
DevOps/MLOps: Docker Kubernetes CI/CD; ML lifecycle tooling such as MLflow/Kubeflow/SageMaker/Azure ML (or equivalent).
Working knowledge of enterprise data platforms / ETL pipelines.
Exposure to enterprise monitoring/ticketing (e.g. Splunk/Datadog/AppDynamics; Jira/ServiceNow) or similar operational toolchains.
Experience working in secure/regulatory environments and adhering to data governance (PII access controls auditability).
Location: Hybrid(Trivandrum/Kochi)
Role: Permanent
Budget: Upto 30LPA
Experience: 8-12 years
Must Have Skills:
8-12 years total including 4-6 years software engineering 4-5 years hands-on AI/ML (overlap acceptable). 2 years technical leadership preferred.
Strong software engineering fundamentals: Python solid backend engineering; ability to integrate with UI layers (web apps) as needed.
Hands-on AI/ML delivery: model development deployment experience across traditional ML and deep learning plus GenAI patterns (RAG prompt engineering evals; fine-tuning is a plus).
Experience building agentic / tool-using LLM systems (or equivalent orchestration patterns) in real implementations.
Cloud proficiency in one: AWS or Azure or GCP (compute storage networking security; managed ML services a plus).
DevOps/MLOps: Docker Kubernetes CI/CD; ML lifecycle tooling such as MLflow/Kubeflow/SageMaker/Azure ML (or equivalent).
Working knowledge of enterprise data platforms / ETL pipelines.
Exposure to enterprise monitoring/ticketing (e.g. Splunk/Datadog/AppDynamics; Jira/ServiceNow) or similar operational toolchains.
Experience working in secure/regulatory environments and adhering to data governance (PII access controls auditability).
Required Skills:
AZUREUIMODEL DEVELOPMENTSAGEMAKERCI/CDDOCKERAIKUBERNETESWEB APPSMLAWSPYTHON
