GEN AI Lead

Job Description

Job Description

Generative AI Lead | 6–8 Years Experience

We're looking for a seasoned Machine Learning Engineer who thrives at the intersection of data, engineering, and business impact. If you love turning messy real-world problems into production-grade AI solutions — this one's for you.

Work Schedule

This is a contract role requiring 2 days onsite per week . Candidates must be able to commute to the office location.

What You'll Do

• Partner directly with business stakeholders to define ML use cases, success metrics, and evaluation frameworks — translating strategy into working models
• Lead end-to-end data workflows: exploration, quality checks, feature engineering, and dataset preparation
• Build, train, and iterate on ML models; run experiments, compare candidates, and champion the best solution
• Package and deploy models into production-ready services using containerization and MLOps best practices
• Own post-deployment health — set up monitoring, track model performance, and drive continuous improvement

Your Technical Toolkit

Languages & Querying Python (hands-on, non-negotiable) · SQL (joins, window functions, CTEs, query optimization)

Machine Learning Regression · Decision Trees · Random Forest · XGBoost · LightGBM · SVM · KNN Model evaluation (Precision/Recall, F1, ROC-AUC, MSE/RMSE) · Hyperparameter tuning · Cross-validation

Deep Learning TensorFlow · Keras · PyTorch · CNNs · RNNs · LSTMs · Transformers Applied to NLP, Computer Vision, and Time-Series Forecasting

Data Engineering Feature engineering · Missing data handling · Outlier detection · Normalization · Data cleaning pipelines

Visualization & BI Matplotlib · Seaborn · Plotly · Tableau · Power BI · Storytelling with data

Cloud & Big Data Spark · Hadoop · AWS (S3, SageMaker, EC2) or Azure (Databricks, Data Factory) or GCP (BigQuery, Vertex AI)

Deployment & MLOps Flask / FastAPI · Docker · Kubernetes (a plus) · CI/CD basics · Airflow / Prefect

Databases MySQL · PostgreSQL · SQL Server · MongoDB · Cassandra

✅ What Sets You Apart

• A solid conceptual grip on supervised and unsupervised learning, with real experimental work to back it up
• Proven experience shipping models to production in cloud-agnostic, API-first architectures
• Comfortable collaborating with engineering teams via version control and CI/CD workflows
• Generative AI exposure is a strong plus — and increasingly central to this role

• Technology, Information and Internet

Contract