Description

You will design and deploy machine learning models and large language model architectures to solve complex business problems.

Responsibilities

• Develop and deploy model pipelines using AWS SageMaker.
• Implement MLOps best practices for model development, deployment, and monitoring.
• Apply statistical learning algorithms and neural networks to real-world datasets.
• Optimize LLM performance through prompt engineering, fine-tuning, and architecture patterns like RAG and FLARE.
• Build and manage vectorized databases for efficient data storage and retrieval.

Required Skills

• 5+ years of professional experience in Machine Learning and Data Science.
• Expert-level Python programming skills.
• Deep understanding of neural networks, transformer algorithms, and open-source LLM foundation models.
• Experience with statistical learning algorithms including GLM, XGBoost, and Random Forest.
• Proficiency with AWS cloud technologies including S3, EC2, and RDS.
• Knowledge of LLM performance evaluation using NLP and LLM-assisted metrics.
• 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.

Key Skills

Education

Bachelor's degree in Computer Science