Model Accuracy Development and Test Engineer (Datacentre AI Engineering)

Qualcomm; Al Khobar; On-site; SAR 150,000 - 200,000; Full time

Job summary

A leading technology company in Saudi Arabia is seeking an Inference Accuracy Engineer to design and validate deep learning model accuracy at scale. The role includes developing Python-based evaluation tools and conducting accuracy tests across multiple frameworks. Ideal candidates will have significant experience in AI/ML, programming skills in Python, and familiarity with inference runtimes like TensorRT and ONNX. This position offers opportunities for career growth and competitive benefits.

Benefits

Salary including housing & transport allowance

Stock (RSU's) and performance related bonus

Paid Maternity Leave

6 weeks fully paid Paternity Leave

Employee stock purchase scheme

Child Education Allowance

Life and Medical Insurance

Health and recreational membership reimbursement

Qualifications

• Strong background in AI/ML model evaluation and accuracy metrics.
• Experience with large language models (LLMs) and generative AI accuracy validation.
• Expertise with inference runtimes (TensorRT, ONNX Runtime, Triton).

Responsibilities

• Define and implement accuracy KPIs across precision modes.
• Develop scalable Python-based accuracy evaluation tools and automated pipelines.
• Execute comprehensive accuracy tests for large-scale models (LLMs, vision, diffusion).
• Document workflows, maintain dashboards, and publish accuracy results.

Skills

AI/ML model evaluation

Model architectures (transformers, CNNs, RNNs)

Large language models (LLMs)

Inference runtimes (TensorRT, ONNX Runtime)

Quantization (INT8/FP8/INT4)

Model graph conversion

Python programming

Statistical methods and visualization tools

Debugging accuracy failures

Education

Bachelor's / Master's degree in Engineering, AI, Information Systems, or related field

Tools

PyTorch

TensorFlow

Kubernetes

Job description

Company:

Qualcomm Middle East Information Technology Company LLC

Job Area:

Engineering Group > Software Test Engineering

General Summary:

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.

About the Role

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. You will have strong problem‑solving ability, excellent Python programming skills, and hands‑on expertise with inference pipelines.

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 / Masters 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
\ paid Maternity Leave
• 6 weeks fully paid Paternity Leave
• Employee stock purchase scheme
• Child Education Allowance
• 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.

References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.

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 [e-mail] 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. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

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