ML Engineer – Test & Learn Platform

Hiring: ML Engineer – Test & Learn Platform Experience: 3+ Years Location: Remote (1–2 visits to Bangalore required) Salary: ₹40,000 – ₹50,000/month --- Role Overview: We are looking for an ML Engineer to build and scale experimentation and causal inference systems. You will work on statistical engines, APIs, and cloud-based pipelines to enable data-driven decision-making. --- Key Responsibilities: - Develop ML/statistical models (DID, Synthetic Control, A/B Testing) in Python - Build and integrate FastAPI-based services - Design large-scale data pipelines using PySpark, Delta Lake, and Azure Data Lake - Optimize Spark jobs (memory, partitioning, performance tuning) - Work with Databricks for job orchestration and data workflows - Containerize and deploy applications using Docker & Kubernetes - Ensure code quality with testing and CI/CD pipelines - Collaborate with data science and product teams --- Must Have Skills: - Python (3.9+), Pandas, NumPy, Scikit-learn, SciPy - Strong PySpark & Spark Internals (OOM handling, tuning, optimization) - Databricks (clusters, workflows, Delta Lake) - Causal Inference: A/B Testing, DID, Hypothesis Testing - API Development (FastAPI or similar) - Azure Cloud (Data Lake, ML services) - Docker & Kubernetes - Testing with PyTest --- Good to Have: - Celery / Redis - Polars, PyArrow, SQLAlchemy - Econometrics / experimental design - CI/CD tools (SonarCloud, Snyk, GitHub Actions) ---