Description

You will develop and deploy generative AI models and machine learning pipelines to solve complex business problems.

Responsibilities

• Develop and deploy model pipelines using AWS SageMaker.
• Implement neural network and transformer algorithms for large language and chat models.
• Apply prompt engineering and fine-tuning techniques to optimize LLM performance.
• Build and manage vectorized databases for efficient data storage and retrieval.
• Monitor LLM performance using NLP and LLM-assisted metrics.

Required Skills

• 3+ years of professional experience in Machine Learning and Data Science.
• Expert proficiency in Python programming.
• Deep understanding of transformer algorithms, LLM architecture patterns (RAG, FLARE), and open source foundation models.
• Experience with statistical learning algorithms including GLM, XGBoost, and Random Forest.
• Strong knowledge of AWS cloud technologies including S3, EC2, and RDS.
• Knowledge of MLOps best practices for model development, deployment, and monitoring.
• Bachelor’s or Master’s Degree in Computer Science or equivalent professional competency.

Preferred Skills

• Data engineering experience with SQL, Spark, or AWS Glue.
• Experience with Docker, Kubernetes, TeamCity, or Terraform for deployment and CI/CD.

Key Skills

Education

Bachelor's degree in Computer Science