Machine Learning Engineer II ( Growth & ML), Hyderabad

Build and maintain end-to-end ML pipelines for training, evaluation, and batch inference targeting identity resolution, audience segmentation, and content affinity.

Develop and optimize production ML infrastructure including feature stores, training workflows, and batch inference integrated with downstream platforms.

Collaborate with senior engineers and cross-functional teams to ensure data quality, pipeline reliability, and document models and experiments clearly.

2–4 years of industry experience in machine learning, data science, or ML engineering (or 1–2 years with a relevant M.S.).

Strong proficiency in Python, including libraries such as pandas, NumPy, scikit-learn, and at least one deep learning framework (PyTorch or TensorFlow).

Experience with Spark/PySpark or equivalent large-scale data processing and proficiency in SQL; familiarity with cloud data warehouses like Snowflake or Databricks.

Bachelor’s degree in Computer Science, Statistics, Engineering, or related quantitative field (or equivalent practical experience).

Experienced in building production ML pipelines and infrastructure at scale, bridging data science and software engineering.

Comfortable using and learning modern ML tools including experiment tracking (MLflow), Databricks, Snowflake, and agentic AI development tools.

Practical understanding of ML lifecycle with strong fundamentals in classification, regression, ranking, embeddings, and model evaluation metrics.