Data Science / AI ML Engineer

About the Role: We are hiring Data Science / AI & ML Engineers (Freshers) to work on compiler frameworks, transformer-based infrastructures, and end-to-end AI pipelines. You will collaborate with research teams to translate mathematical models into optimized execution graphs, implement custom kernels and low-level performance optimizations, and contribute to the development of deep learning frameworks and execution runtimes powering large-scale model training. Education: Any Graduate Key Responsibilities: Design and develop compiler frameworks that optimize AI model execution at the kernel, graph, and operator levels; Architect scalable transformer-based infrastructures for distributed multi-node training and efficient inference; Build end-to-end AI pipelines including graph optimizations, memory scheduling, and compute distribution; Collaborate with research teams to translate mathematical models into optimized execution graphs and intermediate representations (IRs); Implement custom kernels, quantization strategies, and low-level performance optimizations in C/C++ and CUDA; Analyze and tune runtime performance bottlenecks focusing on parallelization, vectorization, and memory management; Develop domain-specific compiler passes for tensor operations, automatic differentiation, and operator fusion; Conduct systematic experiments to explore scaling laws, precision formats, and architectural optimizations for improved computational efficiency; Contribute to the development and optimization of deep learning frameworks and execution runtimes, focusing on tensor computation graphs, distributed training pipelines, and execution scheduling; Work on data and training infrastructure including dataset preparation pipelines, tokenization strategies, preprocessing workflows, and evaluation systems for large-scale model training; Participate in model efficiency research including quantization techniques, sparsity methods, precision formats, and inference optimization for large-scale neural networks Requirements: Strong proficiency in C, C++ or Java, with good command over pointers, memory management, performance optimization, and systems-level programming; Solid foundation in Mathematics - calculus, probability, statistics, and linear algebra; Strong logical reasoning, problem-solving ability, high intelligence (IQ), and an analytical mindset; Ability to operate effectively in a research-driven, high-intensity environment with cross-functional collaboration