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Blubridge
Ai Ml Engineer (Freshers)
Blubridge
Chennai•On-site•Salary•1-3 Yrs•Jun 27
Job description
Overview
Role: AI & ML Engineer (Freshers)
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.
Qualifications
- 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.
- Proficiency or willingness to learn CUDA and Rust for high-performance and systems-level development.
- Understanding of computer architecture, operating systems, parallel computing, and memory hierarchy.
- Familiarity with deep learning frameworks, transformer architectures, or distributed training systems.
Benefits
- A research-driven engineering environment focused on building AI systems and advancing foundational machine learning capabilities.
- Opportunity to contribute to the development of foundation models and the infrastructure required for large-scale training and inference.
- Hands-on exposure to core layers of the AI stack including model architectures, data pipelines, deep learning frameworks, compilers, and runtime systems.
- Access to high-performance compute infrastructure and multi-node GPU clusters for large-scale experimentation and systems research.
- Mentorship and close collaboration with engineering and research teams working on the development of a GPT-scale dense foundation model.
- An environment suited for individuals driven by curiosity, rigorous problem solving, and long-term research-oriented engineering work.
- Competitive salary package
- Employee Stock Ownership Plan (ESOP) eligibility upon confirmation
- Health insurance coverage
- Personal accident and life insurance coverage
- Generous parental leave policy
- Accommodation / transportation allowance
- Complimentary lunch and dinner