Software Engineer II

Role Overview

We are seeking a result-oriented Software Developer with expertise in Generative AI & Large Language Models to design & develop solutions powered by Fujitsu’s new processor, which help solve real-world challenges facing society and businesses across different industries. The role involves building and optimizing LLM, LVM & LMM. The ideal candidate will have knowledge, experience, and passion for both AI models/applications and hardware/software system & should be skilled in back-end development, high-performance computing, AI framework engineering on modern CPU-based architectures.

Responsibilities

• Improve and analyze performance of Generative AI & LLM software applications.
• Enable and optimize OSS/ISV applications for Fujitsu’s new processor, starting with LLM-related applications.
• Develop new algorithms for ML/DL frameworks, tuning technologies and working on software based on the proposed approaches using AI framework engineering.
• Improve and analyze performance of Generative AI & LLM Models for inferencing and fine tuning.
• Understanding of AI model optimization techniques such as operator fusion, quantization & Sparsity.
• Solid understanding of hardware & software systems.
• Troubleshooting, debugging, and fixing bugs and upgrading software/applications.
• Writing technical documentation.
• Learning continually, sharing knowledge, and fostering exchange of skills.
• Working using agile methods (planning meetings, review meetings, standup meetings, development, etc.).
• Working on multiple projects at once while keeping focused on project timeline.

Requirements

You will be able to demonstrate that you have:

• A degree in Computer Science, Engineering, or a related field (Master’s/MTech or PhD preferred).
• Minimum 2 years’ experience in SW development, Deep Learning & AI Frameworks.
• Proficiency with fundamental back-end server-side languages such as Python & C/C++.
• Knowledge in neural compression & quantization techniques such as pruning & knowledge distillation.
• Knowledge of LLM Fine tuning & training techniques (PEFT, LoRA, QAT etc. are preferred).
• Knowledge and experience related to AI Agents, RAG & RLHF Techniques.
• Familiarity with Inference runtimes ONNX Runtime, OpenVINO.
• Experience with Deep learning frameworks such as PyTorch, TensorFlow, JAX, Llama.cp & vLLM.
• Experience in software development in agile approach.
• Strong debugging skills using profiling tools (PyTorch Profiler, TensorFlow Profiler, perf).
• Excellent writing, verbal communication, and teamwork skills.

Preferred Experience:

• Knowledge of hardware-aware optimizations (oneDNN, XLA, ROCm, MLIR, SparseML).
• Contributions to open-source community.
• Publications in International forums / conferences / journals.
• Knowledge and experience in Cloud service (Azure/AWS) features such as Functions, VM, Container, DevOps (CI/CD).
• Great skills in evaluating performance and security of software applications and delivering solutions which are efficient and performant.