Senior ML Engineer

We are looking for a Senior Machine Learning Engineer with strong foundations in
classical machine learning to design, build, and deploy scalable ML solutions that power
data -driven products and platforms. This role involves owning the end -to -end ML lifecycle
from data ingestion and feature engineering to model training, evaluation, and production
deployment while collaborating closely with data engineering, platform, and product
teams.
The ideal candidate is hands -on, production -oriented, and deeply experienced in
regression, classification, and large -scale data processing, with working exposure to
modern Generative AI and LLM platforms as an added advantage.

Design, develop, and deploy ML models for regression, classification, clustering,
and anomaly detection use cases
• Build end -to -end ML pipelines including data extraction, ingestion, preprocessing,
feature engineering, model training, and evaluation
• Work with structured and semi -structured data to enable scalable, high
performance ML systems
• Implement feature engineering, feature selection, normalization, and scaling
techniques for robust model performance
• Deploy and monitor ML models in production using containerized and cloud -native
approaches
• Collaborate with data engineering teams on ETL pipelines, data quality, and data
availability
• Optimize model performance, reliability, and inference latency in real -world
environments
• Contribute to MLOps practices including versioning, CI/CD, monitoring, and
retraining workflows
• Leverage LLM -based solutions where appropriate (e.g., text classification,
enrichment, or hybrid ML + LLM pipelines)

3–5 years of experience building and deploying machine learning solutions in
production environments
• Proven track record of delivering end -to -end ML projects from data to deployment
• Strong problem -solving mindset with the ability to translate business problems into
ML solutions
• Experience working in cross -functional, data -driven teams