Junior Machine-Learning Engineer

Job Description

Join our applied-ML team to help turn data into product features—recommendation engines, predictive scores, and intelligent dashboards that ship to real users. You’ll prototype quickly, validate with metrics, and productionise models alongside senior ML engineers. Day-to-Day Responsibilities Clean, explore, and validate datasets (Pandas, NumPy, SQL) Build and evaluate ML/DL models (scikit-learn, TensorFlow / PyTorch) Develop reproducible pipelines using notebooks → scripts → Airflow / Kubeflow Participate in feature engineering, hyper-parameter tuning, and model-selection experiments Package and expose models as REST/gRPC endpoints; monitor drift & accuracy in prod Share insights with stakeholders through visualisations and concise reports Must-Have Skills 1–2 years building ML models in Python Solid understanding of supervised learning workflows (train/validate/test, cross-validation, metrics) Practical experience with at least one deep-learning framework (TensorFlow or PyTorch) Strong data-wrangling skills (Pandas, SQL) and basic statistics (A/B testing, hypothesis testing) Version-control discipline (Git) and comfort with Jupyter-based experimentation Good-to-Have Familiarity with MLOps tooling (MLflow, Weights & Biases, Sagemaker) Exposure to cloud data platforms (BigQuery, Snowflake, Redshift) Knowledge of NLP or CV libraries (spaCy, Hugging Face Transformers, OpenCV) Experience containerising ML services with Docker and orchestrating with Kubernetes Basic understanding of data-privacy and responsible-AI principles Job Types: Full-time, Permanent Pay: From ₹19,100.00 per month Benefits: Health insurance Life insurance Paid sick time Paid time off Provident Fund Schedule: Fixed shift Monday to Friday Experience: Junior Machine-Learning Engineer: 1 year (Preferred) Work Location: In person