Machine Learning Engineer

We are looking for a Machine Learning Engineer to implement and optimize Nugens Domain-Aligned AI technology that enables predictable performance in industries where mistakes are unacceptable. You will work on implementing our core ML innovations that help enterprises trust decisions made by AI systems in environments, maintaining reliability across specialized knowledge domains. Responsibilities Implement and optimize ML models that maintain quantifiable reliability bounds across specialized knowledge domains. Design and execute experiments to measure and improve domain-specific AI reliability, particularly in legal, financial, and healthcare sector. Develop techniques to provide reliability metrics and confidence scores for regulatory compliance. Collaborate with engineering teams to deploy reliable ML systems that scale efficiently in production environments. Continuously analyze model performance across different domains to identify and address reliability gaps. Requirements Strong ML background with experience implementing and optimizing deep learning models using PyTorch or TensorFlow. Experience with techniques that improve model reliability and performance in production environments. Ability to quickly understand, implement, and iterate on research papers and new techniques in the ML field. Excellent problem-solving skills with bias for action and debugging complex ML systems. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.