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Model Accuracy Development and Test Engineer (Datacentre AI Engineering)
Qualcomm Technologies, Inc
Riyadh
On-site
SAR 100,000 - 140,000
Full time
3 days ago
Be an early applicant

Job summary

A leading technology company in Saudi Arabia is seeking an Inference Accuracy engineer to design, develop, and validate the accuracy of deep learning models deployed at scale. The role involves accuracy analysis, debugging, and optimizing inference processes. Candidates should have a solid background in AI/ML evaluation, experience with relevant tools, and programming skills in Python. The position offers comprehensive benefits, including a salary with housing and transport allowance, stock options, and paid parental leave.

Benefits

Salary including housing & transport allowance
Stock (RSU's) and performance-related bonus
Fully paid Maternity Leave
Fully paid Paternity Leave
Employee stock purchase scheme
Child Education Allowance
Relocation and immigration support
Life and Medical Insurance
Reimbursement for health and recreational memberships

Qualifications

  • Strong background in AI/ML model evaluation and accuracy metrics.
  • Solid understanding of model architectures and their impact on accuracy.
  • Experience with LLMs and generative AI accuracy validation.

Responsibilities

  • Define and implement accuracy KPIs across precision modes.
  • Develop scalable Python-based accuracy evaluation tools.
  • Execute comprehensive accuracy tests for large-scale models.

Skills

AI/ML model evaluation
Model architectures
Accuracy metrics
Inference runtimes
Python
Statistical methods
Quantization techniques

Education

Bachelor’s / Master’s degree in Engineering, Machine learning/ AI, Information Systems, Computer Science

Tools

TensorRT
ONNX Runtime
PyTorch
TensorFlow
Job description
Company

Qualcomm Middle East Information Technology Company LLC

Job Area

Engineering Group, Engineering Group > Software Test Engineering

General Summary

We are seeking an Inference Accuracy engineer to design, develop, and validate model accuracy of deep learning models deployed at scale. The role focuses on deep accuracy analysis, debugging, accuracy evaluation, and recovery during inference on large data‑centre hardware platforms.

About Us

Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including 5G‑enabled smartphones that double as pro‑level cameras and gaming devices, smarter vehicles and cities, and the technology behind the smart, connected factories that manufactured your latest purchase. Qualcomm 5G and AI innovations are the power behind the connected intelligent edge. You’ll find our technologies behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.

Key Responsibilities
  • Define and implement accuracy KPIs across precision modes
  • Develop scalable Python‑based accuracy evaluation tools and automated pipelines
  • Implement accuracy‑preserving optimizations for inference frameworks (TensorRT, ONNX Runtime, AITemplate, Triton)
  • Build and maintain automated pipelines for accuracy evaluation across multiple frameworks (ONNX, TensorFlow, PyTorch)
  • Develop reusable plugins for pre‑processing, post‑processing, and metric evaluation
  • Execute comprehensive accuracy tests for large‑scale models (LLMs, vision, diffusion)
  • Validate accuracy under various quantization and precision settings (FP32, FP16, INT8)
  • Perform accuracy analysis with deep understanding of model architecture, including layers, attention mechanisms, and parameter configurations
  • Identify architecture‑driven accuracy degradation trends and propose optimization strategies
  • Identify issues related to pre‑processing drift, tokenization mismatches, operator fallback, and quantization effects
  • Analyse accuracy differences across hardware targets, firmware versions, and runtime backends
  • Perform slice‑based accuracy analysis (batch size, concurrency, sequence length, domain shifts)
  • Design and run experiments to recover accuracy, including fine‑tuning, calibration, and hyperparameter adjustments
  • Debug accuracy failures by tracing root causes across data pre‑processing, model layers, quantization steps, and deployment pipelines
  • Compare results across different hardware/software stacks and generate actionable insights
  • Document workflows, maintain dashboards, and publish accuracy results for stakeholders
Required Skills & Experience
  • Strong background in AI/ML model evaluation and accuracy metrics
  • Solid understanding of model architectures (transformers, CNNs, RNNs, MoE) and their impact on accuracy
  • Experience with large language models (LLMs) and generative AI accuracy validation
  • Expertise with inference runtimes (TensorRT, ONNX Runtime, Triton)
  • Understanding of quantization (INT8/FP8/INT4), calibration, QAT, and accuracy trade‑offs
  • Experience with model graph conversion (PyTorch → ONNX → backend engines)
  • Hands‑on experience with accuracy pipeline development and automation frameworks; understanding of video generation model accuracy and multi‑modal evaluation benchmarking
  • Proficiency in Python and familiarity with ML toolkits (ONNX Runtime, TensorFlow, PyTorch)
  • Expertise in accuracy analysis, including statistical methods and visualization tools
  • Ability to design experiments for accuracy recovery and debug accuracy failures effectively
  • Knowledge of quantization techniques and mixed‑precision workflows
  • Experience with data‑centre accelerators (NVIDIA A100/H100/B200, AI100 Ultra, Gaudi, TPU)
  • Knowledge of LLM accuracy evaluation tools (lm‑eval, HELM, synthetic benchmarks) is an advantage
  • Strong problem‑solving and analytical skills with the ability to isolate complex accuracy issues
  • Familiarity with distributed deployment systems (Kubernetes, cloud inference services)
Required Qualifications
  • Bachelor’s / Master’s degree in Engineering, Machine learning/ AI, Information Systems, Computer Science, or related field
  • 4-10 years’ of Software Engineering or related work experience
  • 4-10 years’ experience with Programming Language such as C, C++, Python
What's on Offer
  • Salary including housing & transport allowance
  • Stock (RSU's) and performance related bonus
  • 16 weeks fully paid Maternity Leave
  • 6 weeks fully paid Paternity Leave
  • Employee stock purchase scheme
  • Child Education Allowance
  • Relocation and immigration support (if needed)
  • Life and Medical Insurance
  • Live+ Well Reimbursement for health and recreational membership fees
Minimum Qualifications
  • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience
  • Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience
  • PhD in Engineering, Information Systems, Computer Science, or related field
  • 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.
Equal Opportunity

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e‑mail disability‑accommodations@qualcomm.com or call Qualcomm’s toll‑free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities.

Contact

If you would like more information about this role, please contact Qualcomm Careers.

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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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