About the role
Machine Learning Intern Singapore - Careers At TETRAMEM INC --> Career Opportunities with TETRAMEM INC A great place to work. Careers At TETRAMEM INC Share with friends or Subscribe! At TetraMem, we are redefining the future of AI with our groundbreaking innovations in In-Memory Computing. Leveraging world-record multi-level RRAM technology, we deliver highly efficient solutions for AI computations, enabling superior performance and energy efficiency across applications ranging from edge devices to data centers. Our talented team of engineers and industry-leading executives drives this progress, making TetraMem a leader in advanced memory technologies. If you are passionate about cutting-edge technology and thrive in a fast-paced, collaborative environment, TetraMem is the place for you. Join our global team to shape the future of AI computations and sustainable technology solutions while working at the forefront of innovation. Together, we can make a lasting impact. Are you ready for new challenges and new opportunities? Join our team! Current job opportunities are posted here as they become available. Subscribe to our RSS feeds to receive instant updates as new positions become available. --> --> --> Back To Openings Machine Learning Intern (Singapore) Department: Software - ML & Algorithm Location: San Jose, CA START YOUR APPLICATION
About
the Role We are seeking a Software Intern to support the development of tools, frameworks, and applications that enable neural network models to run efficiently on TetraMem�s novel analog compute-in-memory chips. This is an exciting opportunity to work at the intersection of software, hardware, and artificial intelligence.
Responsibilities
Responsibilities Develop, optimize, and maintain Python and C++ software for neural network model compression, conversion, deployment, and runtime environments. Design and implement tools to improve machine learning model efficiency, including quantization, pruning, graph optimization, and memory reduction techniques. Analyze and adapt machine learning models to improve compatibility, performance, and power efficiency on Compute-in-Memory (CIM) and Analog AI hardware architectures. Develop software frameworks, APIs, and runtime components to support end-to-end AI model deployment on edge AI and embedded systems. Perform software design, implementation, debugging, testing, and performance profiling to optimize system throughput, latency, and resource utilization. Collaborate closely with AI researchers, hardware engineers, and system architects to validate hardware-software co-design and system-level functionality. Evaluate emerging machine learning models, algorithms, and deployment techniques to enhance AI inference performance on next-generation semiconductor platforms. Participate in code reviews, establish software quality standards, and contribute to automated testing, continuous integration, and technical documentation. Troubleshoot software and system issues across the AI stack, including model conversion pipelines, runtime environments, and hardware acceleration frameworks. Contribute to the development of innovative AI computing technologies and support research activities through technical presentations, publications, patents, and cross-functional collaboration.