About the company we are looking for: is a deep tech focused on building energy-efficient fast Edge AI engines particularly targeting the latest laptop chips with CPU, integrated GPU, and NPU.
Job Description:
Role Overview: As an Applied AI Researcher, you will focus on low-level optimizations to accelerate AI inference and fine-tuning, leveraging advanced techniques and frameworks. You will work closely with our technical team to implement efficient execution across heterogeneous architectures (CPU, GPU, and NPU).
Responsibilities:
Research and develop low-level optimizations for AI inference and fine-tuning across heterogeneous architectures.
Optimize PyTorch-based workloads for efficient execution, including kernel fusion, quantization, pruning, and sparsity techniques.
Work on cross-device execution strategies, ensuring efficient computation distribution between CPU, GPU, and NPU.
Implement memory and computation optimizations, such as caching strategies and tensor layout transformations.
Improve latency, throughput, and energy efficiency of real-time AI workloads.
Collaborate with software engineers to integrate optimizations into production pipelines.
Stay up to date with the latest advancements in AI inference, hardware acceleration, and Reinforcement Learning (RL) techniques (a plus).
Requirements:
5-7 years of experience in AI research, optimization, or systems engineering.
Strong expertise in PyTorch, including TorchScript, TorchDynamo, and other acceleration techniques.
Proficiency in low-level optimization techniques, such as vectorization, memory optimization, and CUDA/OpenCL programming.
Experience with model compression techniques like quantization, pruning, and knowledge distillation.
Familiarity with AI compilers (e.g., TensorRT, TVM, XLA, MLIR, Triton).
Understanding of heterogeneous computing architectures (CPU/GPU/NPU) and their interaction with AI workloads.
Strong background in numerical computing, profiling, and performance tuning.
Experience with ONNX, TensorFlow, JAX, or other ML frameworks is a plus.
Knowledge of Reinforcement Learning (RL) is a significant advantage.
Nice to Have:
Experience with Intels OpenVINO or other vendor-specific acceleration frameworks.
Contributions to open-source AI/ML projects.
Familiarity with distributed training and inference techniques.
Research publications in ML systems, optimization, or inference acceleration.
Other Details
Location: Lahore.
Experience: 5-7 years
Working Days &Timings: Monday to Friday (timing depends on the project)
Apply at jobs@hrways.co (not com)
About HR Ways:
"HR Ways is an Award winning Technical Recruitment Firm helping software houses and IT Product companies internationally and locally to find IT Talent. HR Ways is engaged by 300+ Employers worldwide ranging from worlds biggest SaaS Companies to most competitive Startups. We have entities in Dubai, Canada, US, UK, Pakistan, India, Saudi Arabia, Portugal, Brazil and other parts of the world. Join our Whatsapp Channel https://shorturl.at/983az to stay updated or visit www.hrways.co to know more."