Deep Learning Compiler Engineer

About Us

Deccan AI Experts is a pioneering AI company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in high-quality human-curated data, AI-first operations, and advanced AI evaluation systems. Our global network of technology experts helps train and evaluate next-generation AI models through expert engineering judgment and domain-specific expertise.

About the Role

We are seeking a Deep Learning Compiler Engineer (Freelancer) to support advanced AI evaluation initiatives focused on deep learning compilers, graph optimization, model compilation, AI accelerators, compiler infrastructure, and AI-generated technical content evaluation.

In this role, you will evaluate AI-generated compiler optimizations, computational graph transformations, model lowering strategies, code generation workflows, inference optimization techniques, and technical documentation. Your expertise will help improve AI systems designed for compiler engineering, AI infrastructure, model optimization, and high-performance deep learning deployment.

This position is ideal for professionals with experience in deep learning compilers, compiler engineering, AI infrastructure, machine learning systems, GPU programming, or high-performance computing.

Responsibilities

• Review AI-generated compiler code, graph optimization strategies, intermediate representations (IR), model conversion workflows, benchmarking reports, and architecture documentation.
• Evaluate optimization techniques involving graph rewriting, kernel fusion, operator scheduling, quantization, mixed precision, memory planning, tensor optimization, and hardware-specific compilation.
• Verify AI-generated recommendations for model optimization across CPUs, GPUs, NPUs, TPUs, and custom AI accelerators.
• Assess compiler pipelines for correctness, maintainability, portability, and performance.
• Identify optimization opportunities, compiler bugs, numerical inconsistencies, hardware compatibility issues, memory inefficiencies, and execution bottlenecks.
• Provide structured feedback to improve AI performance in compiler engineering, deep learning optimization, and AI systems development.
• Review peer-developed deliverables to maintain quality and consistency standards.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, Mathematics, or a related field is required.
• Master's degree or Ph.D. in Computer Science, Compiler Engineering, Artificial Intelligence, Machine Learning, High-Performance Computing, or a related discipline is preferred.
• 3+ years of hands-on experience in compiler engineering, deep learning infrastructure, AI systems, GPU programming, or performance optimization.
• Developing or optimizing compiler pipelines for machine learning workloads.
• Optimizing computational graphs and inference performance.
• Working with compiler intermediate representations and code generation frameworks.
• Reviewing AI-generated compiler code and optimization strategies.
• Benchmarking and profiling AI models across different hardware architectures.
• Experience with technologies such as LLVM, MLIR, TVM, TensorRT, XLA, ONNX Runtime, OpenVINO, Apache TVM, Triton, Glow, IREE, oneDNN, CUDA, cuDNN , or similar compiler and inference optimization frameworks.
• Familiarity with deep learning frameworks including PyTorch, TensorFlow, JAX , and model formats such as ONNX is preferred.
• Experience with profiling tools such as Nsight Compute, Nsight Systems, VTune, perf , or equivalent performance analysis tools.
• Excellent analytical thinking, systems programming, compiler design, and written English communication skills.
• Strong attention to detail and ability to evaluate production-grade compiler systems.
• Ability to work independently in a remote, fast-paced environment.

Preferred Qualifications

• Experience working with semiconductor companies, AI hardware vendors, cloud providers, compiler teams, AI startups, research laboratories, or high-performance computing organizations.
• Expertise in one or more areas such as LLM inference optimization, graph compilers, distributed model execution, quantization-aware compilation, custom AI accelerators, runtime systems, or heterogeneous computing.
• Experience evaluating AI-generated compiler code, optimization reports, architecture documents, or performance benchmarking results.
• Familiarity with Generative AI, prompt engineering, RLHF (Reinforcement Learning from Human Feedback), AI benchmarking, compiler-assisted optimization, or AI systems evaluation is highly desirable.
• Contributions to open-source compiler frameworks (LLVM, MLIR, TVM, IREE, Triton, etc.), technical publications, patents, or conference presentations are a plus.
• Professional certifications or advanced training in compiler engineering, CUDA programming, AI infrastructure, or cloud computing are advantageous.

Why Join Us

• Competitive hourly pay: ₹2,000/hour
• Fully remote with flexible working hours.
• Opportunity to contribute to cutting-edge AI initiatives in deep learning infrastructure, compiler engineering, and Generative AI.
• Exposure to advanced AI systems focused on graph optimization, model compilation, AI accelerators, and large-scale inference.
• Flexible project-based opportunities with global teams.
• Work on next-generation AI solutions supporting cloud platforms, semiconductor companies, AI infrastructure providers, research organizations, and enterprise AI deployments.