Responsibilities:- Develop, maintain, and optimize software components within TetraMem's compiler, runtime, and SDK toolchain for analog compute-in-memory (CIM) hardware.
- Work closely with senior engineers to translate machine learning models into efficient executable workloads for TetraMem's AI accelerator architecture.
- Implement software features, debugging tools, and low-level optimizations to improve inference latency, throughput, memory utilization, and power efficiency.
- Support the integration of machine learning frameworks, model conversion pipelines, and deployment workflows for customer applications.
- Collaborate with compiler, machine learning, hardware, and validation teams to resolve software issues and improve overall system performance.
- Assist in benchmarking, profiling, and analyzing AI workloads to identify performance bottlenecks and recommend optimization opportunities.
- Support hardware bring-up, software validation, and demonstration of AI applications on TetraMem compute-in-memory platforms.
- Write clean, maintainable, and well-documented production-quality code while following software engineering best practices.
- Participate in design reviews, code reviews, testing, and continuous improvement of the compiler and runtime software stack.
- Stay current with advances in compiler technologies, AI frameworks, machine learning deployment, and computer architecture to continuously improve TetraMem's software platform.
QualificationsRequired Qualifications- Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
- Experience developing embedded software for microcontroller-based or embedded computing platforms.
- Strong programming skills in C/C++ for embedded systems and/or Python for machine learning application development.
- Solid understanding of software engineering principles, data structures, algorithms, and debugging techniques.
- Strong analytical and problem-solving skills with the ability to learn new technologies quickly.
- Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced, cross-functional startup environment.
- Self-motivated with the ability to work independently while contributing to team objectives.
Preferred Qualifications- Experience training, optimizing, quantizing, or deploying machine learning models on resource-constrained or edge AI hardware platforms.
- Experience developing compiler technologies, code generation, or machine learning model compilation.
- Experience with CI/CD pipelines, automated testing, and software release processes.
- Programming experience in Rust.
- Experience developing firmware for RTOS-based embedded systems, including integration with platforms such as Zephyr or FreeRTOS.
- Hands-on experience with edge AI platforms, embedded AI accelerators, or custom AI hardware.
- Experience using software profiling, debugging, and performance analysis tools to optimize low-level systems.
- Familiarity with Linux development environments, Git version control, and modern software development workflows.
Salary Range:$135,000 - $165,000 annually, plus full-time employee benefits and equity eligibility.