Job Description

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).

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