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

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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.

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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

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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

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Good to Have:

- Celery / Redis
- Polars, PyArrow, SQLAlchemy
- Econometrics / experimental design
- CI/CD tools (SonarCloud, Snyk, GitHub Actions)

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Interested candidates can share their profiles.