GEN AI Lead

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

Industry

Technology, Information and Internet

Employment Type

Contract