AI ML Engineer

About the Opportunity
A fast-moving, innovation-driven organization in the Enterprise AI & Machine Learning sector, we build and deploy scalable ML-powered solutions that drive automation, predictive analytics, and intelligent decision-making across industries. Our ML Engineers work at the intersection of algorithmic rigor and real-world product impact—transforming raw data into high-accuracy, production-grade models used by thousands of users daily. Role & Responsibilities

• Design, train, and deploy machine learning models—classification, regression, clustering—for live business use cases across domains.


• Build and optimize end-to-end ML pipelines: data ingestion ➜ feature engineering ➜ model training ➜ inference ➜ monitoring.


• Collaborate with data engineers to integrate ML models into scalable cloud infrastructure (AWS/GCP/Azure).


• Implement and evaluate model performance using metrics such as precision, recall, F1-score, AUC-ROC, and business-specific KPIs.


• Develop model explainability and fairness tooling to support auditability and stakeholder trust.


• Automate retraining, drift detection, and model versioning using CI/CD workflows and MLOps best practices.

Skills & Qualifications

Must-Have

• Python


• Scikit-learn


• Pandas


• NumPy


• TensorFlow


• PyTorch


• MLflow


• Git

Preferred

• Experience with Hugging Face Transformers


• Familiarity with AWS SageMaker or GCP Vertex AI


• Knowledge of XGBoost / LightGBM / CatBoost

Benefits & Culture Highlights

• Opportunity to work on high-impact, customer-facing AI/ML products with measurable ROI.


• Collaborative, feedback-rich environment with mentorship from senior ML architects.


• On-site culture with flexible core hours, team lunches, and quarterly hackathons.