ML Ops

Prior

~2+ years

of experience working with ML Ops & DS

Responsibilities & Skills :

Deploy, monitor, and scale ML models on

AWS (SageMaker, EKS, Lambda)

or

GCP (Vertex AI, GKE, Cloud Functions) .

Build and maintain

CI / CD pipelines

for ML workflows using

GitHub Actions / Jenkins / cloud-native tools .

Containerize and orchestrate workloads with

Docker & Kubernetes ; manage infra via

Terraform / CloudFormation .

Implement

model registries, feature stores, and observability

using

MLflow, Feast, Prometheus / Grafana .

Collaborate with data scientists to operationalize ML models for

personalization, recommendations, NLP .

Proficient in

Python , ML frameworks ( Scikit-learn, TensorFlow, PyTorch ) and data pipelines ( Airflow, Spark, SQL ).

Bonus : experience with

real-time ML serving, A / B testing, or media / recommender systems .

Nice-to-Have : Experience with

subscription, media, or recommender systems .

Knowledge of

experiment design & causal inference .

Exposure to

real-time ML serving

(KFServing, Seldon, Ray Serve).

Education : Btech / Mtech