ML Engineer

Position: ML Engineer (CE50SF RM 4206)

Shift timing : 02 PM to 10 PM

Work Mode : Work From Office

Required Industry Experience : 5+ years of total development experience

Relevant Experience required : 2.5+ years of relevant Gen AI experience

Education Required: Bachelor s / Masters / PhD: Bachelor s degree in engineering

Must have skills

• Python for ML
• Scikit-learn, PySpark
• Supervised Learning Logistic Regression, Random Forest, XGBoost/LightGBM/CatBoost, calibration
• Unsupervised Learning & Anomaly Detection, Imbalanced Data Techniques Class weighting, focal loss, threshold tuning, cost-sensitive learning
• Model Evaluation & Calibration, Statistics & Probability
• Drift Monitoring Data drift, concept drift, PSI, KL divergence, model performance monitoring, retraining strategies
• ML Architecture Design End-to-end pipelines
• Databricks Notebooks, Delta Lake, Jobs, Workflows, Feature Store, MLflow integration, Unity Catalog,

MLOps Fundamentals

Good to have skills: • Experience in Azure

• Deep Learning PyTorch / TensorFlow, sequence models (LSTM/Transformers) for fraud detection
• Git-based workflows (branching, pull requests, code reviews) and Agile/Scrum delivery

Any special or skills related notes • Hands-on and accountable for delivering working, supportable solutions

• Clear communicator who can translate between business needs and technical implementation
• Quality-focused (testing, monitoring, documentation) with attention to reliability and maintainability
• Calm under pressure when responding to incidents and prioritizing production work
• Ownership & accountability across the full ML lifecycle
• Mentoring other team members / knowledge sharing

Role focus: Core ML modelling Key responsibilities

• Design ML architecture (feature store, training pipelines, scoring)
• Build: o Supervised diversion-risk model o Unsupervised anomaly detection model o Model evaluation, calibration, and drift monitoring
• Define reusable feature engineering framework
• Design response schema:

o Risk score o Explainability layer

Required skills

• Strong Python (scikit-learn, PySpark)
• Experience with anomaly detection techniques
• Experience with imbalanced datasets (fraud/risk domains preferred)
• Knowledge of MLOps (Databricks preferred)

Job Category: Digital_Cloud_Web Technologies

Job Type: Full Time

Job Location: Pune Ahmedabad Indore

Experience: 5+ years

Notice period: 0-15 days

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.