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<b>Job Title: ML Engineer – Experimentation Platform<br></b><b>Experience:</b> 3 – 4 Years
<p></p><b>Location:</b> Remote<br> <b>Notice Period:</b> Immediate Joiners Only<br> <br><b>About the Role</b><br>We are looking for a highly skilled ML Engineer to join our Test & Learn Platform team. In this role, you will build and scale experimentation and causal inference services that enable business teams to make data-driven decisions globally.<br>
<p></p>
<p>You will work across statistical modeling, API development, cloud-native infrastructure, and large-scale data processing to deliver reliable and production-ready ML solutions.<br></p>
<p><b>Key Responsibilities</b><br></p>
<ul>
<li>Develop and maintain statistical and machine learning modules for:<br></li>
<ul>
<li>Difference-in-Differences (DID)<br></li>
<li>Synthetic Control<br></li>
<li>A/B Testing<br></li>
<li>Multi-Treatment Effects<br></li>
</ul>
<li>Build and extend RESTful APIs using FastAPI and integrate them with web applications through SDK wrappers<br></li>
<li>Design and optimize large-scale data pipelines using PySpark, Delta Lake, and Azure Data Lake<br></li>
<li>Diagnose and resolve Out-of-Memory (OOM) issues in PySpark workloads by optimizing:<br></li>
<ul>
<li>Memory allocation<br></li>
<li>Partitioning<br></li>
<li>Broadcast joins<br></li>
<li>Caching strategies<br></li>
<li>Spark configurations<br></li>
</ul>
<li>Deploy and manage Databricks workloads including notebooks, job clusters, and Delta Lake tables<br></li>
<li>Containerize and deploy services using Docker, Kubernetes, and CI/CD pipelines<br></li>
<li>Ensure code quality, testing, and security using PyTest, SonarCloud, and Snyk<br></li>
<li>Collaborate closely with Data Scientists and Product teams to convert research concepts into scalable production systems<br></li>
<li> <br></li>
</ul>
<p><b>Mandatory Skills</b><br></p>
<ul>
<li>Strong experience in Python (3.9+)<br></li>
<li>Hands-on expertise in:<br></li>
<ul>
<li>PySpark & Spark Internals<br></li>
<li>Databricks<br></li>
<li>FastAPI / API Development<br></li>
<li>Azure Cloud Platform<br></li>
<li>Kubernetes & Docker<br></li>
<li>PyTest<br></li>
</ul>
<li>Strong understanding of:<br></li>
<ul>
<li>DID<br></li>
<li>Synthetic Control<br></li>
<li>A/B Testing<br></li>
<li>Hypothesis Testing<br></li>
<li>Panel Data Methods<br></li>
</ul>
<li>Expertise in statistical and ML libraries:<br></li>
<ul>
<li>statsmodels<br></li>
<li>scikit-learn<br></li>
<li>SciPy<br></li>
<li>Pandas<br></li>
<li>NumPy<br></li>
</ul>
</ul>
<p><b>Technical Requirements</b><br></p>
<p><b>PySpark & Spark Internals</b><br></p>
<ul>
<li>Strong understanding of Spark memory model<br></li>
<li>Executor tuning and shuffle optimization<br></li>
<li>Diagnosing and resolving OOM errors<br></li>
<li>Experience with:<br></li>
<ul>
<li>Broadcast thresholds<br></li>
<li>Partition skew handling<br></li>
<li>Spill-to-disk optimization<br></li>
<li> <br></li>
<li>GC tuning<br></li>
</ul>
</ul>
<p><b>Databricks</b><br></p>
<ul>
<li>Hands-on experience with:<br></li>
<ul>
<li>Job orchestration<br></li>
<li>Cluster configuration<br></li>
<li>Notebook workflows<br></li>
<li>Delta Lake optimization<br></li>
<li>Z-ordering, compaction, and caching<br></li>
</ul>
</ul>
<p><b>Cloud & DevOps</b><br></p>
<ul>
<li>Azure Storage, Azure ML, and Azure Data Lake<br></li>
<li>Docker-based containerization<br></li>
<li>Kubernetes orchestration for ML workloads<br></li>
<li>CI/CD pipeline integration<br></li>
</ul>
<p><b>Testing & Quality</b><br></p>
<ul>
<li>Unit and integration testing using PyTest<br></li>
<li>Familiarity with SonarCloud, Snyk, and GitHub Actions<br></li>
</ul>
<p><b>Good-to-Have Skills</b><br></p>
<ul>
<li>Experience with Celery and Redis for async task orchestration<br></li>
<li>Familiarity with Polars, PyArrow, or SQLAlchemy<br></li>
<li>Background in econometrics or experimental design<br></li>
<li>Experience with Spark UI profiling and performance benchmarking<br></li>
<li>Knowledge of advanced CI/CD tooling and automation practices<br></li>
</ul>
<p><b>Preferred Candidate Profile</b><br></p>
<ul>
<li>Strong analytical and problem-solving abilities<br></li>
<li>Ability to work independently in a remote setup<br></li>
<li>Excellent collaboration and communication skills<br></li>
<li>Passion for building scalable ML and experimentation platforms<br></li>
</ul>
<p><b>Tech Stack</b><br></p>
<p></p><b>Languages & Libraries:</b> Python, Pandas, NumPy, SciPy, statsmodels, scikit-learn<br> <b>Big Data:</b> PySpark, Spark Internals, Delta Lake<br> <b>Cloud & Platforms:</b> Azure, Databricks, Azure Data Lake<br><b>APIs & Backend:</b> FastAPI<br> <b>DevOps:</b> Docker, Kubernetes, GitHub Actions<br> <b>Testing & Security:</b> PyTest, SonarCloud, Snyk<br> <br>
<p></p><br><br>
