Machine Learning Engineer

Role: AI Engineer with expertise in data governance, automated data policy management, data quality, data tagging cloud implementation, and optimization of Large Language Models (LLMs). This role focuses on designing secure, scalable cloud solutions, implementing robust data governance frameworks, and leveraging LLMs to enhance the management and processing of unstructured data.

Experience:

• 5+ years of experience in AI/ML, data governance, and cloud implementation.
• Proven expertise in managing unstructured data and implementing automated data tagging methodologies.
• Hands-on experience with cloud platforms (AWS, Azure, Google Cloud) and big data technologies (e.g., Databricks, AWS Sage Maker, AWS Bedrock).
• Proficiency in programming languages such as Python, Java, and SQL.
• Strong understanding of data governance frameworks, data privacy regulations, and security best practices.
• Strong Understanding with AI/ML frameworks (e.g., PyTorch, Keras, Scikit Learn) and LLM optimization techniques.
• Strong programming skills in languages such as Python, R,
• Knowledge of NLP, RAG technologies, Agentic AI and data transformation processes for unstructured data.
• Experience with data lake or Lakehouse platforms (e.g., Azure Blob Storage, AWS S3, Databricks).
• Certifications in cloud security (e.g., AWS Security Specialty).
• Knowledge of MLOps and automated policy compliance tools.
• Familiarity with AI-driven data contract generation and enforcement frameworks.