AI & ML Engineer/ Data Science/ Research - C/C++ Programmer(Freshers)

Role

Vacancies

Education:

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.
  

Required Skills & Qualifications:

• Strong proficiency in

  C

  and

  C++

  (mandatory).
• Experience or strong interest in compiler construction, runtime systems, and code generation.
• Proficiency or willingness to learn CUDA and Rust for high-performance computing and systems-level development.
• Solid foundation in Mathematics calculus, probability, statistics, and linear algebra.
• Deep understanding of computer architecture, operating systems, data structures, and memory management.
• Analytical mindset with strong debugging and performance profiling abilities.
• Ability to thrive in a fast-paced, research-oriented environment with cross-functional collaboration.

What We Offer:

• A dynamic and innovative work environment with a AI research-driven team.
• Mentorship, learning, and growth opportunities in AI infrastructure and systems research.
• Competitive compensation with performance-based advancement and technical ownership.
• Opportunity to work on compiler-level AI framework design and large-scale foundation model optimization.
• Access to multi-node GPU clusters and next-gen compute environments for experimentation.
  

Important: