Junior Machine Learning Engineer

Launch your ML career where your curiosity ships to production from day one. You will work alongside senior engineers on real-world ML problems, building features, running experiments, and shipping models to production while being mentored every step of the way. This is a hands-on role where you will be contributing to models that real users interact with immediately. Assist in building and iterating on ML models under guidance. Write clean, well-tested Python code for data preprocessing, feature engineering, and model evaluation. Explore datasets through Exploratory Data Analysis (EDA) to surface insights and data quality issues. Run A/B and offline experiments, documenting and presenting findings. Maintain and improve existing ML pipelines, including fixing bugs and optimizing performance. Collaborate with data engineers to access, clean, and transform training data. Participate actively in code reviews and sprint ceremonies.

Key Focus:

Learn, execute, and grow under mentorship.

Required Skills:

0-5 years of professional or project-based experience in ML/data science. Proficiency in Python, including NumPy, Pandas, and scikit-learn, plus familiarity with a deep learning framework (PyTorch or TensorFlow). Solid grounding in ML fundamentals, including regression, classification, and evaluation metrics. Familiarity with SQL for querying databases and experience using Jupyter Notebooks for analysis. Working knowledge of Git and collaborative development workflows. Valuable Experience (Nice to Have): Internship, capstone, or Kaggle competition experience. Exposure to cloud platforms (AWS, GCP, or Azure). Familiarity with experiment tracking tools (MLflow or Weights & Biases).