Description

You will design, build, and maintain machine learning systems and data pipelines. You own the end-to-end lifecycle from feature engineering to model deployment.

Responsibilities

• Develop and deploy ML models using PyTorch, TensorFlow, and scikit-learn.
• Build scalable data pipelines and process large datasets with PySpark and Databricks.
• Implement GenAI solutions, including RAG architectures and semantic search.
• Design recommendation systems and conduct A/B testing to validate model performance.
• Perform rigorous feature engineering and data preprocessing.

Required Skills

• 5+ years of experience in data science or machine learning engineering.
• Proficiency in Python for scripting and model development.
• Hands-on experience with PySpark and Databricks for distributed data processing.
• Strong knowledge of deep learning frameworks: PyTorch and TensorFlow.
• Experience with classical ML libraries: scikit-learn.
• Practical application of Generative AI, RAG, and recommendation systems.
• Bachelor’s degree in a quantitative field or equivalent experience.

Preferred Skills

• Experience with Hugging Face libraries for NLP tasks.
• Background in implementing semantic search solutions.

Key Skills

Education

Any Gradute