Description

You will design, build, and deploy end-to-end machine learning and generative AI solutions, from data preparation to production monitoring.

This role is on-site.

Responsibilities

• Develop and deploy ML models using Python, scikit-learn, TensorFlow, PyTorch, or Keras.
• Implement MLOps practices including model versioning, CI/CD pipelines, monitoring, and automated deployments.
• Build and support Generative AI use cases, leveraging Prompt Engineering, RAG, embeddings, vector databases, and LLM evaluation frameworks.
• Perform statistical analysis, feature engineering, and model validation to optimize performance.
• Collaborate with stakeholders to translate business requirements into scalable AI/ML solutions.

Required Skills

• 8+ years of experience in Data Science, Machine Learning, and advanced analytics.
• Strong proficiency in Python and hands-on expertise with scikit-learn.
• Experience with deep learning frameworks: TensorFlow, PyTorch, or Keras.
• Knowledge of cloud platforms for ML deployment (AWS, Azure, or GCP).
• Proven ability to deliver end-to-end ML solutions from data prep to production.
• Experience with LLMs, Generative AI, RAG, and vector databases.
• Bachelor's degree in a relevant field.

Key Skills

Education

Bachelor's degree