Lead the design, development, and deployment of ML solutions at scale. Drive architecture, mentor the team, and integrate advanced AI (including LLMs) into enterprise workflows.
Must-Have
(Mandatory)
------------------------------
Machine Learning:
Deep understanding of supervised, unsupervised, and reinforcement learning, model evaluation, and feature engineering.
Deep Learning:
Proficiency with
TensorFlow, PyTorch, Keras
; hands-on with
CNNs, RNNs
.
Programming:
Expert in
Python
(NumPy, Pandas, scikit-learn, etc.);
R
exposure acceptable.
Big Data Technologies:
Practical experience with
Spark
(Databricks preferred); familiarity with
Hadoop/Kafka
.
Cloud Platforms:
Azure or AWS or GCP
(ML services, data storage, compute), with strong
MLOps
exposure.
Data Warehousing & Databases:
Strong
SQL
,
NoSQL
, and data modeling.
Drift Detection & Monitoring:
Hands-on experience with model drift detection, monitoring, and automated alerts.