Machine Learning Engineer

Responsibilities

• Design and implement advanced prompt engineering strategies, including ToT, CoT, and other optimization methods
• Fine-tune pre-trained foundational models using AWS services such as Amazon SageMaker and AWS Bedrock
• Develop and optimize ML workflows for efficient training, inference, and deployment
• Leverage JumpCloud for identity and security management within the ML environment
• Collaborate with data scientists, engineers, and business stakeholders to integrate AI-driven solutions
• Monitor model performance and continuously refine prompts and training methodologies

Requirements

• 3+ years of experience in machine learning, AI, or NLP
• Proficiency in prompt engineering with a focus on Tree of Thought (ToT) and Chain of Thought (CoT)
• Hands-on experience in fine-tuning and deploying models using Amazon SageMaker and AWS Bedrock
• Strong programming skills in Python, TensorFlow, or PyTorch
• Experience working with AWS cloud services for model training and deployment
• Familiarity with JumpCloud and cloud-based identity/security management

Preferred Qualifications

• Experience in large-scale AI model training and optimization
• Knowledge of LLM architectures and optimization techniques
• Experience in data engineering and feature engineering for ML models
• Familiarity with MLOps best practices