Job Description

? 5+ years experience ? 1 Position ?Job Information: ?Work Experience: 5+ years Industry: IT Services Job Type: FULL TIME Location: Mohali/Noida/Bengaluru , India ?Job Summary: ? 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: ? 5+ 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. ?Interview Process ?Technical Assessment ?Technical Round 1 ?Technical Round 2