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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.
