Job Title

Job Summary Personal Characteristics Strong portfolio and excellent attitude. Must be self-confident to work in a Team and to handle the responsibilities individually as well Should be a good listener/ Can articulate well / Good Communication Skills Ability to work with teams across organizational boundaries, different cultures and different time zones in a virtual environment Delivery oriented and able to work under strict deadlines. We are seeking an experienced Machine Learning to join our AI-driven project. The ideal candidate will have a strong background in prompt engineering techniques such as Tree of Thought (ToT) and Chain of Thought (CoT), along with hands-on expertise in fine-tuning foundational models using AWS services like Amazon SageMaker and AWS Bedrock. The role requires a deep understanding of AI/ML workflows and the ability to implement advanced prompt optimization methods to enhance model performance. Key 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 for better accuracy. Stay updated with the latest research and trends in prompt engineering and ML fine-tuning. Required Qualifications 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, PyTorch, or similar ML frameworks. Experience working with AWS cloud services for model training and deployment. Familiarity with JumpCloud and cloud-based identity/security management. Strong analytical and problem-solving skills with an ability to work in cross-functional teams. 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.