software engineer

sales engineer

ai engineer

engineer

materials engineer

ai system engineer

HALA

<div>
 <p>
  <strong>
   Who Are We
  </strong>
 </p>
 <p>
  <br/>
  HALA is a leading fintech player in the MENAP region that aims to redefine financial services and build the future bank of SMEs. HALA aims at empowering SMEs to start, run, and grow their businesses by providing them with cutting-edge financial and technological tools.
 </p>
 <p>
  <br/>
  HALA currently holds multiple entities in UAE, Saudi Arabia and Egypt (including HALA Payments and HALA Logistics) and offers solutions that enable merchants to digitize their payments as well as manage their sales and operations.
 </p>
 <p>
  <br/>
  Founded in 2017, HALA is currently licensed by the Saudi Arabian Central Bank.
 </p>
 <p>
  &nbsp;
 </p>
 Job Summary
 <p>
  The Software/AI Engineer , Compliance Technology is responsible for designing, developing, and maintaining technology, automation, and AI-enabled solutions that enhance the effectiveness, efficiency, and governance of Compliance operations. The role translates regulatory and business requirements into scalable technical solutions and supports areas including AML, KYC, fraud prevention, regulatory reporting, risk, and governance. The position also contributes to the responsible adoption of AI through appropriate governance, risk assessment, monitoring, and human oversight.
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  &nbsp;
 </p>
 Responsibilities&nbsp;
 <ul>
  <li>
   Design and develop technology solutions that automate and enhance Compliance processes.
  </li>
  <li>
   Build AI-powered tools to improve compliance monitoring, investigations, and regulatory reporting.
  </li>
  <li>
   Develop and maintain integrations, APIs, and internal applications supporting Compliance systems.
  </li>
  <li>
   Identify automation opportunities and translate compliance requirements into technical solutions.
  </li>
  <li>
   Implement AI, workflow automation, and RegTech solutions to improve operational efficiency.
  </li>
  <li>
   Develop dashboards and analytics that support compliance decision-making and regulatory reporting.
  </li>
  <li>
   Ensure solutions comply with cybersecurity, data privacy, and regulatory requirements.
  </li>
  <li>
   Collaborate with Compliance, Technology, Risk, and Information Security teams on system enhancements.
  </li>
  <li>
   Maintain and optimize compliance applications, ensuring reliability, performance, and scalability.
  </li>
  <li>
   Support audits and regulatory examinations by providing technical documentation and system evidence.
  </li>
  <li>
   Research and recommend emerging AI and compliance technologies to drive continuous improvement.
  </li>
  <li>
   Establish and maintain AI governance controls for Compliance use cases, ensuring responsible, transparent, and compliant use of AI technologies.
  </li>
  <li>
   Conduct AI risk assessments to identify and mitigate risks related to model accuracy, bias, data privacy, security, and regulatory compliance.
  </li>
  <li>
   Monitor and validate AI models and automated solutions on an ongoing basis to ensure accuracy, effectiveness, reliability, and appropriate human oversight.
  </li>
  <li>
   Ensure data quality and governance across Compliance systems and AI solutions, including data accuracy, integrity, access controls, and auditability.
  </li>
  <li>
   Leverage AI and automation to support regulatory change management, including identifying regulatory updates, assessing their impact, and supporting implementation and tracking of required actions.
  </li>
 </ul>
 <p>
  &nbsp;
 </p>
 <p>
  &nbsp;
 </p>
 <strong>
  What We Offer You
  <br/>
 </strong>
 <strong>
  We believe you will love working at HALA!
 </strong>
 <ul>
  <li>
   We have an inclusive and diverse culture that encourages innovation and flexibility in remote, in-office, and hybrid work setups.
  </li>
  <li>
   We offer highly competitive compensation packages, including the potential for shares.
  </li>
  <li>
   We prioritize personal development and offer regular training and an annual learning stipend to tackle new challenges and grow your career in a hyper-growth environment.
  </li>
  <li>
   Join a talented team of over 30 nationalities working in 7 countries and gain valuable experience in an exciting industry.
  </li>
  <li>
   We offer autonomy, mentoring, and challenging goals that create incredible opportunities for both you and the company.
  </li>
  <li>
   You will be given a lot of responsibility and trust.&nbsp;We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.
  </li>
 </ul>
 &nbsp;
 <strong>
  If you think you have what it takes to join a remarkable team #apply_now&nbsp;
 </strong>
 <p>
  &nbsp;
 </p>
</div>


AI & System Engineer

Accenture

<div><div><div><p><b>YOU ARE</b></p></div><div><p>
As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle &mdash; assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps &amp; MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.</p></div><div><p><b>
THE WORK</b></p></div><div><ul><li><p>
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions</p></li></ul></div><div><ul><li><p>
Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps &amp; MLOps</p></li></ul></div><div><ul><li><p>
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC</p></li></ul></div><div><ul><li><p>
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites</p></li></ul></div></div><div><div><ul><li><p>
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production</p></li></ul></div><div><ul><li><p>
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools</p></li></ul></div><div><ul><li><p>
Justify the value of model approaches in business problems</p></li></ul></div><div><ul><li><p>
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production</p></li></ul></div></div></div>
<br>
<div><div><p><b>EDUCATION</b></p></div><div><ul><li><ul><li>Bachelor's Degree or equivalent</li></ul></li></ul></div><div><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p></div><div><ul><li><p>
Proven experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.</p></li></ul></div><div><ul><li><p>
Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming</p></li></ul></div><div><ul><li><p>
Hands-on experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks</p></li></ul></div><div><ul><li><p>
Experience in building and deploying AI/ML based software to a cloud environment.</p></li></ul></div><div><p><b>
PREFERRED QUALIFICATION</b></p></div><div><ul><li><p>
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..</p></li></ul></div><div><ul><li><p>
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.</p></li></ul></div><div><ul><li><p>
Experience with the following programming languages: Python, C++, Java, R, SQL</p></li></ul></div><div><ul><li><p>
Strong written &amp; verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders</p></li></ul></div><div><ul><li><p>
Strong client-facing skillsets in a consulting environment</p></li></ul></div><div><ul><li><p>
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams</p></li></ul></div><div><ul><li><p>
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation</p></li></ul></div><div><ul><li><p>
MS or PhD in related field preferred (computer science, engineering, etc.)</p></li></ul></div></div>

AI & Machine Learning Consultant

Tabby | تابي

<div>
 <strong>
  Department:
 </strong>
 Customer Happiness, Engineering
 <br/>
 <br/>
 <strong>
  Employment Type:
 </strong>
 Internship
 <br/>
 <br/>
 <strong>
  Location:
 </strong>
 KSA
 <br/>
 <br/>
 <strong>
  Description
  <br/>
  <br/>
 </strong>
 Tabby builds financial products used by millions of users across the GCC. Alongside core fintech products, we are actively building internal platforms for AI agents and LLM-based automation used across the company.
 <br/>
 <br/>
 This internship is not educational by default. It is an engineering-adjacent role with real production impact.
 <br/>
 <br/>
 The AI Agents Platform team builds an internal platform that allows teams across Tabby to create, run, evaluate, and iterate on AI agents. These agents automate real human workflows: customer support, operations, fraud checks, data validation, and internal tooling.
 <br/>
 <br/>
 The platform is young, evolving fast, and already used by multiple teams. The internship is designed for candidates who are comfortable working in ambiguous, experimental environments and can think in systems rather than isolated tasks.
 <br/>
 <br/>
 Key Responsibilities
 <br/>
 <br/>
 This is not a demo or experimentation-only role. Interns work on real agents, workflows, and internal tools.
 <br/>
 <br/>
 <ul>
  <li>
   Build AI agents and automations using internal no-code and low-code tooling
  </li>
  <li>
   Configure agent workflows, tools, and orchestration logic
  </li>
  <li>
   Integrate agents with internal systems via APIs and tools
  </li>
  <li>
   Participate in designing agent architectures and workflows
  </li>
  <li>
   Help test, evaluate, and iterate on agent behavior and quality
  </li>
  <li>
   Work with datasets and evaluation results to improve agent performance
  </li>
  <li>
   Document agent logic, workflows, and best practices
  </li>
  <li>
   Work closely with platform engineers, product managers, and internal users
  </li>
  <li>
   Strong logical and systems thinking
  </li>
  <li>
   Ability to break down human workflows into structured steps
  </li>
  <li>
   Understanding of how web services, APIs, and tools interact
  </li>
  <li>
   Experience with no-code or low-code platforms
  </li>
  <li>
   Basic understanding of data formats (JSON), APIs, and webhooks
  </li>
  <li>
   Ability to reason about edge cases, failure modes, and correctness
  </li>
  <li>
   High level of ownership and responsibility
  </li>
  <li>
   Comfort with fast iteration and experimental environments
  </li>
  <li>
   English sufficient for documentation and team communication
  </li>
  <li>
   Experience with LLMs, AI agents, or automation
  </li>
  <li>
   Experience building internal tools or automations
  </li>
  <li>
   Experience with Python
  </li>
  <li>
   Education in data science, machine learning field
  </li>
  <li>
   Understanding of prompt design or agent orchestration concepts
  </li>
  <li>
   Familiarity with evaluation, testing, or quality metrics
  </li>
  <li>
   Curiosity about AI system behavior and limitations
  </li>
  <li>
   Expert-level knowledge of LLMs, agent frameworks, or prompt engineering
  </li>
  <li>
   Prior professional AI, automation, or platform engineering experience
  </li>
  <li>
   Mastery of all listed no-code platforms or LLM tooling
  </li>
  <li>
   Deep knowledge of ML internals, model training, or RAG architectures
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Skills, Knowledge &amp; Expertise
 <br/>
 <br/>
 <ul>
  <li>
   Saudi nationals only
  </li>
  <li>
   Self-funded internship by Tabby
  </li>
  <li>
   We welcome both current students and fresh grads
  </li>
  <li>
   We expect a full-time level of engagement throughout the internship. The program is not part-time: interns should be ready to contribute at a full working-day pace. We understand that students may occasionally need flexibility for classes or exams, which can be aligned with the mentor in advance, but overall performance, ownership, and context involvement are expected at a full-time level.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Format
 <br/>
 <br/>
 <ul>
  <li>
   Paid internship
  </li>
  <li>
   Full integration into the automations building team
  </li>
  <li>
   Distributed engineering team across multiple countries
  </li>
  <li>
   Open to Saudi nationals (Saudi passport required); location flexible &mdash; candidates may be based outside KSA
  </li>
  <li>
   Office-first in Riyadh where possible
  </li>
  <li>
   Clear path to a junior AI automation, no-code engineer, or platform role based on performance
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 This internship is intentionally demanding and designed for candidates aiming for fast professional growth in AI agents and automation engineering.
</div>


AI Intern

<div>
 <p>
  <strong>
   Department:
  </strong>
  Customer Happiness, Engineering
 </p>
 <p>
  <strong>
   Location:
  </strong>
  KSA
  <br/>
  <br/>
 </p>
 <strong>
  Description
  <br/>
  <br/>
 </strong>
 About the companyTabby builds financial products used by millions of users across the GCC. Alongside core fintech products, we are actively building internal platforms for AI agents and LLM-based automation used across the company.
 <br/>
 <br/>
 This internship is not educational by default. It is an engineering-adjacent role with real production impact.
 <br/>
 <br/>
 ContextThe AI Agents Platform team builds an internal platform that allows teams across Tabby to create, run, evaluate, and iterate on AI agents. These agents automate real human workflows: customer support, operations, fraud checks, data validation, and internal tooling.
 <br/>
 <br/>
 The platform is young, evolving fast, and already used by multiple teams. The internship is designed for candidates who are comfortable working in ambiguous, experimental environments and can think in systems rather than isolated tasks.
 <br/>
 <br/>
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 What you will doThis is not a demo or experimentation-only role. Interns work on real agents, workflows, and internal tools.
 <br/>
 <br/>
 <ul>
  <li>
   Build AI agents and automations using internal no-code and low-code tooling
  </li>
  <li>
   Configure agent workflows, tools, and orchestration logic
  </li>
  <li>
   Integrate agents with internal systems via APIs and tools
  </li>
  <li>
   Participate in designing agent architectures and workflows
  </li>
  <li>
   Help test, evaluate, and iterate on agent behavior and quality
  </li>
  <li>
   Work with datasets and evaluation results to improve agent performance
  </li>
  <li>
   Document agent logic, workflows, and best practices
  </li>
  <li>
   Work closely with platform engineers, product managers, and internal users
  </li>
 </ul>
 Required
 <ul>
  <li>
   Strong logical and systems thinking
  </li>
  <li>
   Ability to break down human workflows into structured steps
  </li>
  <li>
   Understanding of how web services, APIs, and tools interact
  </li>
  <li>
   Experience with no-code or low-code platforms
  </li>
  <li>
   Basic understanding of data formats (JSON), APIs, and webhooks
  </li>
  <li>
   Ability to reason about edge cases, failure modes, and correctness
  </li>
  <li>
   High level of ownership and responsibility
  </li>
  <li>
   Comfort with fast iteration and experimental environments
  </li>
  <li>
   English sufficient for documentation and team communication
  </li>
 </ul>
 Strong plus
 <ul>
  <li>
   Experience with LLMs, AI agents, or automation
  </li>
  <li>
   Experience building internal tools or automations
  </li>
  <li>
   Experience with Python
  </li>
  <li>
   Education in data science, machine learning field
  </li>
  <li>
   Understanding of prompt design or agent orchestration concepts
  </li>
  <li>
   Familiarity with evaluation, testing, or quality metrics
  </li>
  <li>
   Curiosity about AI system behavior and limitations
  </li>
 </ul>
 What we do not expect
 <ul>
  <li>
   Expert-level knowledge of LLMs, agent frameworks, or prompt engineering
  </li>
  <li>
   Prior professional AI, automation, or platform engineering experience
  </li>
  <li>
   Mastery of all listed no-code platforms or LLM tooling
  </li>
  <li>
   Deep knowledge of ML internals, model training, or RAG architectures
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Skills, Knowledge &amp; Expertise
  <br/>
  <br/>
 </strong>
 Eligibility
 <ul>
  <li>
   Saudi nationals only
  </li>
  <li>
   Self-funded internship by Tabby
  </li>
  <li>
   We welcome both current students and fresh grads
  </li>
  <li>
   We expect a full-time level of engagement throughout the internship. The program is not part-time: interns should be ready to contribute at a full working-day pace. We understand that students may occasionally need flexibility for classes or exams, which can be aligned with the mentor in advance, but overall performance, ownership, and context involvement are expected at a full-time level.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Format
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Paid internship
  </li>
  <li>
   Full integration into the automations building team
  </li>
  <li>
   Distributed engineering team across multiple countries
  </li>
  <li>
   Open to Saudi nationals (Saudi passport required); location flexible &mdash; candidates may be based outside KSA
  </li>
  <li>
   Office-first in Riyadh where possible
  </li>
  <li>
   Clear path to a junior AI automation, no-code engineer, or platform role based on performance
  </li>
 </ul>
 This internship is intentionally demanding and designed for candidates aiming for fast professional growth in AI agents and automation engineering.
 <br/>
 <br/>
</div>


MASTER-WORKS

<div><p>Master Works is looking for an <b>Agentic AI, Engineer </b>to join our growing team and design, build, and deploy agentic AI systems that can plan, reason, and act. The role covers both single-agent and multi-agent systems, as well as orchestration of workflows involving retrieval-augmented generation (RAG), context engineering, reasoning, tool calling, memory, and inter-agent communication. This role is ideal for a strong software engineer with hands-on AI/ML development experience and a passion for transforming generative AI models into reliable, goal-driven systems capable of solving complex, real-world business problems.</p><p></p>
Key Responsibilities:<p></p><ul><li>
Architect, build, and deploy agentic AI systems that integrate AI agents with foundation models, enterprise systems, third-party tools, and APIs using established agentic frameworks or custom-built orchestrators.</li><li>
Build and maintain retrieval-augmented generation (RAG), memory, and reasoning pipelines that ground agent decisions in reliable, real-world data and enable persistent, contextual, and adaptive behavior.</li><li>
Design single-agent and multi-agent workflows, including planning, delegation, tool selection, handoffs, inter-agent communication, and human-in-the-loop controls.</li><li>
Optimize orchestration and reasoning performance while balancing autonomy, latency, cost, interpretability, reliability, and maintainability.</li><li>
Collaborate with Generative AI engineers, application engineers, MLOps engineers, and product teams to move agentic AI solutions from prototype to production.</li><li>
Monitor, evaluate, and benchmark agent performance, and help ensure AI systems are safe, accurate, trustworthy, observable, and capable of delivering a high-quality user experience.</li><li>
Document agent architectures, communication flows, guardrails, context-engineering strategies, memory design, tool interfaces, and orchestration logic to ensure clarity and reproducibility.</li><li>
Stay current with advances in agentic AI, multi-agent orchestration, RAG, model-context protocols, cognitive architectures, evaluation methods, and AI safety mechanisms.</li><li>
Collaborate with cross-functional teams to design and deliver complete AI solutions for customers.</li></ul><br>
<b>
Requirements</b><br>
<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related field.</li><li>
2+ years of hands-on experience developing agentic AI systems, LLM-powered applications, or advanced Generative AI solutions.</li><li>
Preferably 5+ years of overall professional software engineering experience</li><li>
Contributions to open-source agentic AI frameworks, orchestration platforms, evaluation tooling, or agent communication protocols.</li><li>
Experience building microservices and deploying AI applications on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).</li><li>
Experience with AI safety, guardrails, observability, traceability, evaluation, and explainability for agentic AI systems.</li><li>
Experience deploying LLM or agentic workloads in production using containers, Kubernetes, CI/CD pipelines, and modern MLOps or LLMOps practices.</li></ul><p></p><p><b>
Job Location: </b>HQ</p></div>

Agentic AI, Engineer

Lenovo

<div><div><div><div><h3 class="jobSectionHeader"><b>General Information
</b></h3></div></div><div><div><div><div>Req #
</div><div>WD00104349
</div></div><div><div>Career area:
</div><div>Engineering
</div></div><div><div>Country/Region:
</div><div>Saudi Arabia
</div></div><div><div>City:
</div><div>Riyadh
</div></div><div><div>Date:
</div><div>Wednesday, August 26, 2026
</div></div><div><div>Working time:
</div><div>Full-time
</div></div><div><div><b>Additional Locations</b>:
<ul><li>Saudi Arabia</li></ul>
</div></div></div></div></div><div><div><div><h3 class="jobSectionHeader"><b>Why Work at Lenovo
</b></h3></div></div><div><div><div><div><div><div>We are Lenovo. We do what we say. We own what we do. We WOW our customers.</div><div></div><div><br>
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world&rsquo;s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo&rsquo;s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).</div></div><br>
<div></div><br>
<div>This transformation together with Lenovo&rsquo;s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.</div>
</div></div></div></div></div><div><div><div><h3 class="jobSectionHeader"><b>Description and Requirements
</b></h3></div></div><div><div><div><div><div><p>Support QE engineer on new project NPI activities: document review, sample tracking, first‑article inspection follow‑up, test data collection &amp; sorting.</p><p>
协助 QE 工程师开展新产品导入 NPI 工作：资料核对、样品跟进、首件检验跟进、测试数据收集整理。</p></div><p></p><div><p>
Assist to compile quality documents: control plan, FMEA, inspection SOP, quality report, 8‑D report draft preparation.</p><p>
协助编制质量文件：控制计划、FMEA、检验 SOP、质量报告，起草 8‑D 报告初稿。</p></div><p></p><div><p>
Track production quality abnormal issues: collect defect photos, failure data, coordinate with production/engineering/supplier for countermeasure implementation, track improvement status.</p><p>
跟进产线质量异常：收集不良照片、失效数据，协同生产 / 工程 / 供应商落实改善对策，跟踪改善进度。</p></div><p></p><div><p>
Support incoming, in‑process &amp; outgoing quality verification; assist IQC/OQC for sample re‑check and evidence keeping.</p><p>
协助来料、过程、出货质量验证，配合 IQC/OQC 做样品复判与证据留存。</p></div><p></p><div><p>
Conduct regular quality data statistics: defect rate, reject rate, monthly quality KPI raw data sorting.</p><p>
完成日常质量数据统计：不良率、报废率，月度质量 KPI 原始数据整理。</p></div><p></p><div><p>
Support customer quality related work: sort customer complaint information, organize complaint record, assist QE for customer reply material preparation.</p><p>
支持客户质量相关工作：整理客诉信息、建立客诉台账，协助 QE 准备客户回复资料。</p></div><p></p><div><p>
Participate in internal quality audit, QCC activity, non‑conformity item follow‑up &amp; closure.</p><p>
参与内部质量审核、QCC 品质改善活动，跟进不符合项闭环。</p></div><p></p><div><p>
Complete other temporary tasks assigned by QE supervisor.</p><p>
完成上级交办的其他临时质量工作。</p></div>
</div></div><div><div><div><i>We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.</i></div>
</div></div></div></div></div><div></div><div><div><div><div><div><b>Additional Locations</b>:
<ul><li>Saudi Arabia</li></ul>
</div></div><div><ul><li>Saudi Arabia<br>
</li></ul></div><div></div><div><div><div><br>
<br>
<div><b>AI PROCESSING NOTICE</b></div><div></div><div><br>
We use AI-based tools to support some of our processes (e.g. online interviews recordings and transcripts) in order to achieve better efficiency, accuracy and for our documentation purposes. AI can make mistakes, but we always make sure that the outputs are manually reviewed by a human. You can always opt-out or contact us in case of any question.</div></div></div></div></div></div></div></div>

Lab Assistant QE

Qualcomm

<div>
 <strong>
  <strong>
   Company:
   <br/>
   <br/>
  </strong>
 </strong>
 Qualcomm Middle East Information Technology Company LLC
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   Job Area:
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 Engineering Group, Engineering Group &gt; Systems Engineering
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   General Summary:
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  About us
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 Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region
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 As Saudi Arabia accelerates its digital transformation under Vision 2030, Qualcomm is investing in world‑class computing and data centre capabilities to power AI, cloud, and advanced connectivity at scale. This is a unique opportunity to work in a fast‑growing technology hub, supporting critical environments and helping shape the future of data centre operations in the Kingdom and beyond.
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   About The Role
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 The Qualcomm AI team is developing hardware and software for Machine Learning solutions spanning the data center, edge, infrastructure, automotive markets and beyond.
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 We are seeking a Senior Staff Machine Learning Engineer to provide hands‑on technical leadership in the design, optimization, and deployment of machine learning frameworks and applications on Qualcomm AI platforms. This is an individual contributor role that operates with broad technical scope, high autonomy, and significant cross‑team impact. The successful candidate will drive complex initiatives end‑to‑end, influence technical direction through expertise and execution, and mentor engineers across the organization while remaining deeply hands‑on.
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 Job activities span the full product life cycle, from early research and architecture through commercial deployment and sustained optimization. The role requires frequent cross‑functional collaboration, strong technical judgment, and the ability to independently plan, execute, and influence complex engineering efforts.
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  We are looking for candidates with12+ years Systems Engineering or related work experience
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   Responsibilities Will Include:
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   Research, design, develop, enhance, and implement the different components of machine learning frameworks, Graph optimizations for performance and accuracy tailored towards Qualcomm NPUs.
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   Analyze software requirements, determine the feasibility of design within the given constraints, consult with architecture and HW engineers, and implement software solutions best suited for Qualcomm's SOCs.
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   Analyze and identify system level integration issues, interface with the software development, integration and test teams.
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   Work on latest GenAI techniques and adapt those for NPUs. Architect new techniques which work best on Qualcomm SOCs and architecture.
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   Provide technical leadership and mentorship through design reviews, architectural guidance, and hands‑on collaboration, influencing best practices without direct people‑management responsibility
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   Minimum Qualifications
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   bachelor&rsquo;s degree in engineering, Information Systems, Computer Science, or related field.
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   12+ years Systems Engineering or related work experience.
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   Required Qualifications
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   Has internal working knowledge of Machine learning frameworks like Pytorch, Tensorflow.
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   Has experience in model level optimization using techniques like torch compile.
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   Expertise in model architecture, backed by literature rationale and intuition
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   Understanding of broad-spectrum model architectures across modalities, ML algorithms and techniques
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   Expertise in Model training and inference workflows.
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   Hands-on Experience in C/C++, Python development (5+ years)
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   Hands-on Experience with Object Orientated Design, and software development practices in general
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   Experience with Source Code and Configuration management tools, git knowledge is required
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   Preferred Qualifications And Aptitudes
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   Willingness to work in a cohesive software development environment with ability to work on low level implementation (code &amp; test) and interfacing with hardware and simulators
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   Experience in neural network architectures + ML compiler workload synthesis, a plus
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   Prior working experience of hardware accelerators and hardware software co-design
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   Experience of profiling software and optimization techniques
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   Passion to drive to develop leading-edge "deep learning" framework and algorithms working on mobile and embedded platforms.
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   A research mindset with expertise in software development
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   What's On Offer
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 Apart from working with great people, we offer the below:
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   Salary including housing &amp; transport allowance
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   Stock (RSU's) and performance related bonus
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   16 weeks fully paid Maternity Leave
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   6 weeks fully paid Paternity Leave
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   Employee stock purchase scheme
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   Child Education Allowance
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   Relocation and immigration support (if needed)
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   Life and Medical Insurance
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   Live+ Well Reimbursement for health and recreational membership fees
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   Minimum Qualifications:
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   Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.
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 Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.
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 OR
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 PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
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   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.
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 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-accomodations@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. (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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 Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
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  To all Staffing and Recruiting Agencies
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 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
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 If you would like more information about this role, please contact Qualcomm Careers.
</div>


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