Highlights
Research-driven engineering environment, access to high-performance compute infrastructure, hands-on exposure to core layers of AI stack.
Description
Job Summary
pWe are seeking fresh graduates to join our team as AI & ML Engineers. As an integral part of the R&D division, you will be involved in designing and developing compiler frameworks that optimize AI model execution at various levels. You’ll work on scalable transformer-based infrastructures for distributed training and efficient inference, building end-to-end pipelines for graph optimizations and more.
Responsibilities
- Design and develop compiler frameworks optimizing AI models' execution at kernel, graph, and operator levels
- Architect scalable transformer-based infrastructures for multi-node training and 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 IRs
- Implement custom kernels, quantization strategies, and 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 experiments to explore scaling laws, precision formats, and architectural optimizations for improved computational efficiency
- Work on data and training infrastructure including dataset preparation pipelines, tokenization strategies, and evaluation systems for large-scale model training
Required Skills
- C/C++ Programming
- Mathematics (Calculus, Probability)
- Problem Solving & Logical Reasoning
- Research & Development
- Deep Learning Frameworks
Required Skills Explained
- Strong proficiency in C, C++ or Java with good command over pointers, memory management, performance optimization, and systems-level programming.
- Solid foundation in Mathematics including calculus, probability, statistics, and linear algebra.
- High logical reasoning, problem-solving ability, high intelligence (IQ), and an analytical mindset.
- Experience or strong interest in compiler construction, runtime systems, and code generation is advantageous.
- Proficiency or willingness to learn CUDA and Rust for high-performance and systems-level development.
- Familiarity with computer architecture, operating systems, parallel computing, and memory hierarchy.
- Understanding of deep learning frameworks, transformer architectures, or distributed training systems is beneficial.
Who is this for
pThis role is ideal for fresh graduates with a strong interest in AI and machine learning, especially those who are excited about working on cutting-edge technology and contributing to the development of foundation models. Ideal candidates should have a solid foundation in mathematics and programming.
Why This Job is a Good Opportunity
ulliWork in a research-driven environment focused on building AI systems and advancing foundational machine learning capabilities.liOpportunity to contribute to the development of foundation models and large-scale infrastructure for training and inference.liHands-on exposure to core layers of the AI stack, including model architectures, data pipelines, deep learning frameworks, compilers, and runtime systems.liAccess to high-performance compute infrastructure and multi-node GPU clusters for research and experimentation.liMentorship from engineering and research teams working on a GPT-scale dense foundation model.
Interview Preparation Tips
- Review key concepts in C, C++, Java, and other relevant programming languages to demonstrate strong proficiency.
- Prepare examples of how you have used mathematical principles (calculus, probability, statistics) in problem-solving scenarios.
- Demonstrate your logical reasoning and problem-solving skills with real-life case studies or past projects.
- Research current trends in AI and ML, especially in areas like compiler construction, runtime systems, and deep learning frameworks.
- PRACTICE coding problems related to performance optimization, memory management, and parallel computing.
Career Growth in This Role
pThe role of an AI & ML Engineer offers significant career growth potential. As you advance, you can take on more complex projects that involve optimizing large-scale models and developing new algorithms. Collaborating with research teams will provide opportunities to work on cutting-edge technologies and contribute to the development of foundation models. Additionally, your skills in performance optimization, parallel computing, and systems-level programming make you well-positioned for leadership roles within AI/ML engineering.
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Skills
Frequently Asked Questions
What is the role of an AI & ML Engineer?An AI & ML Engineer designs and develops compiler frameworks that optimize AI models' execution, builds end-to-end pipelines for graph optimizations, and works on distributed training infrastructures.
Do I need prior experience to apply?No, this role is open to fresh graduates with a strong interest in AI and machine learning. Prior experience in relevant areas will be advantageous but not mandatory.
What are the key skills required for this position?Key skills include proficiency in C/C++ programming, a solid foundation in mathematics, problem-solving abilities, research and development, and familiarity with deep learning frameworks.
