civil engineer

mechanical engineer

architectural engineer

data scientist

technical enablement lead

deep learning engineer

Qualcomm

<div><h2 class="jobSectionHeader"><b>Company:
</b></h2>Qualcomm Middle East Information Technology Company LLC
<p></p><h2 class="jobSectionHeader"><b>Job Area:
</b></h2>Engineering Group, Engineering Group &gt; Software Engineering
<p></p><p><b>General Summary:
</b></p><p></p><div><div><p><b>About Us
</b></p></div><div><p>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 intelligent edge devices, next-generation computing platforms, and advanced AI solutions. Qualcomm&rsquo;s leadership in AI, high ‑ performance compute, and connectivity is driving innovation across cloud, edge, and data center environments - delivering scalable, power ‑ efficient platforms that power the next generation of intelligent infrastructure.<br>
</p></div><p></p><div><p><b>About the Role
</b></p></div><div><p>Qualcomm is seeking <b>Machine Learning Applications Engineer </b><b>&ndash; AI </b><b>Inference &amp; Model Optimization </b>to support the enablement of rack-scale deep learning workloads on advanced Qualcomm AI inference accelerator s . These accelerators utilize Qualcomm's expertise in hardware-accelerated AI to deliver high-performance, energy-efficient generative AI and computer vision inference solutions for modern data centers.
</p></div><p></p><div><p>This is a <b>customer </b>‑ <b>facing, highly technical role </b>focused on <b>porting, optimizing, and validating </b><b>deep learning </b><b>AI models </b>on production systems, and enabling Qualcomm&rsquo;s partners to develop and deploy advanced machine learning applications - including computer vision, speech, generative AI and state of the art multimodal reasoning models - using popular frameworks such as PyTorch , TensorFlow, and ONNX on Qualcomm Cloud AI accelerators. Key responsibilities include evaluating models for throughput, latency, and accuracy; profiling and optimizing model performance; building robust application pipelines; integrating customer frameworks; and contributing to documentation, training, and demonstrations.
</p></div><p></p><div><p>The role requires strong expertise in AI models, quantization, performance optimization, and deployment, plus the ability to shape architecture, workload sizing, and system design. It also requires experience with deep learning model development across hardware platforms, solid programming skills, collaboration with cross-functional teams, and proficiency in machine learning frameworks, Linux, and container orchestration tools.
</p></div><p></p><div><p>The ideal candidate can effectively <b>bridge AI model requirements hardware capabilities customer expectations </b>, guiding customers from <b>model selection hardware sizing deployment decisions production readiness.
</b></p></div><p></p><div><p><b>What You&rsquo;ll Do
</b></p></div><div><p><b>A) AI Model Porting &amp; Optimization
</b></p></div><div><ul><li><p>Deploy, optimize and scale deep learning AI models onto accelerator ‑ based data center platforms, including:
</p></li></ul></div><div><ul><li><p>Model conversion workflows
</p></li></ul></div><div><ul><li><p>Quantization techniques (INT8 / mixed precision)
</p></li></ul></div><div><ul><li><p>Runtime integration and optimization
</p></li></ul></div><div><ul><li><p>Integrate ML models onto Qualcomm&rsquo;s Cloud AI ML stack from frameworks such as PyTorch , TensorFlow, and ONNX.
</p></li></ul></div><div><ul><li><p>Drive improvements in <b>model </b><b>throughput </b><b>, </b><b>latency </b><b>, and accuracy </b>, with clear trade ‑ off analysis.
</p></li></ul></div><div><ul><li><p>Build, test, and deploy scalable inference pipelines using serving frameworks such as vLLM , TGI, and Triton.
</p></li></ul></div><div><ul><li><p>Optimize workloads for LLM and GenAI models across both multi-SoC and multi-card architectures.
</p></li></ul></div></div><div><div><ul><li><p>Collaborate with engineering teams to analyze and refine training and inference for advanced deep learning applications.
</p></li></ul></div><div><ul><li><p>Identify bottlenecks across compute, memory, and runtime, and guide optimization strategies.
</p></li></ul></div><div><ul><li><p>Contribute to Qualcomm&rsquo;s Cloud AI GitHub repository and developer documentation, sharing technical best practices and solutions.
</p></li></ul></div><div><ul><li><p>Develop and integrate end-to-end ML application pipelines with customer frameworks and libraries.<br>
</p></li></ul></div><p></p><div><p><b>B) Customer </b>‑ <b>Facing Technical Engagement
</b></p></div><div><ul><li><p>Act as a <b>trusted technical advisor </b>for customers deploying AI workloads.
</p></li></ul></div><div><ul><li><p>Engage in <b>hardware sizing and architecture discussions </b>, aligning model requirements with infrastructure capabilities.
</p></li></ul></div><div><ul><li><p>Provide technical guidance on:
</p></li></ul></div><div><ul><li><p>AI model selection
</p></li></ul></div><div><ul><li><p>Deployment feasibility
</p></li></ul></div><div><ul><li><p>System architecture and performance expectations
</p></li></ul></div><div><ul><li><p>Lead discussions on <b>model capabilities and limitations </b>based on real customer use cases.<br>
</p></li></ul></div><p></p><div><p><b>C) Model&ndash;Infrastructure Alignment
</b></p></div><div><ul><li><p>Assess and evaluate AI model requirements and recommend <b>alternative model approaches </b>when necessary.
</p></li></ul></div><div><ul><li><p>Align model characteristics (latency, throughput, accuracy) with <b>accelerator and system capabilities </b>.
</p></li></ul></div><div><ul><li><p>Connect <b>model requirements </b>with:
</p></li></ul></div><div><ul><li><p>Memory constraints
</p></li></ul></div></div><div><div><ul><li><p>Accelerator architecture
</p></li></ul></div><div><ul><li><p>Scaling limitations
</p></li></ul></div><div><ul><li><p>Support customers in defining <b>model selection strategies based on deployment realities </b>.<br>
</p></li></ul></div><p></p><div><p><b>D) Performance &amp; Scalability Engineering
</b></p></div><div><ul><li><p>Evaluate performance characteristics of AI models in production scenarios, including:
</p></li></ul></div><div><ul><li><p>Throughput expectations
</p></li></ul></div><div><ul><li><p>Latency targets
</p></li></ul></div><div><ul><li><p>Concurrency behavior
</p></li></ul></div><div><ul><li><p>Guide architecture decisions around:
</p></li></ul></div><div><ul><li><p>Scaling strategies (horizontal vs vertical)
</p></li></ul></div><div><ul><li><p>Hardware deployment sizing
</p></li></ul></div><div><ul><li><p>Contribute to discussions on:
</p></li></ul></div><div><ul><li><p>Workload scalability limits
</p></li></ul></div><div><ul><li><p>Impact of model selection on system performance and efficiency
</p></li></ul></div><div><ul><li><p>Provide insights into <b>capacity planning and infrastructure optimization </b>.<br>
</p></li></ul></div><p></p><div><p><b>E) End </b>‑ <b>to </b>‑ <b>End AI Pipeline Design
</b></p></div><div><ul><li><p>Drive discussions around <b>end </b>‑ <b>to </b>‑ <b>end AI pipelines </b>, including:
</p></li></ul></div><div><ul><li><p>Multi ‑ model workflows (e.g., detection + tracking + recognition)
</p></li></ul></div></div><div><div><ul><li><p>Data preprocessing and post ‑ processing stages
</p></li></ul></div><div><ul><li><p>Guide decisions on video and data processing stacks, including:
</p></li></ul></div><div><ul><li><p>Video pipeline choices (e.g., FFMPEG vs GStreamer )
</p></li></ul></div><div><ul><li><p>Integration into inference pipelines
</p></li></ul></div><div><ul><li><p>Ensure pipelines are aligned with:
</p></li></ul></div><div><ul><li><p>Performance requirements
</p></li></ul></div><div><ul><li><p>Hardware capabilities
</p></li></ul></div><div><ul><li><p>Real ‑ time constraints<br>
</p></li></ul></div><p></p><div><p><b>F) Model Trade </b>‑ <b>off Analysis &amp; Validation
</b></p></div><div><ul><li><p>Highlight and explain trade ‑ offs between:
</p></li></ul></div><div><ul><li><p>Accuracy vs compatibility
</p></li></ul></div><div><ul><li><p>Model quality vs deployment feasibility
</p></li></ul></div><div><ul><li><p>Support decision ‑ making on:
</p></li></ul></div><div><ul><li><p>Model simplification vs performance gains
</p></li></ul></div><div><ul><li><p>Precision vs efficiency trade ‑ offs
</p></li></ul></div><div><ul><li><p>Lead or support <b>model capability validation </b>in deployment environments.
</p></li></ul></div><div><ul><li><p>Collaborate with customers to define:
</p></li></ul></div><div><ul><li><p>Inference assumptions
</p></li></ul></div><div><ul><li><p>Model sizing strategies for large ‑ scale workloads<br>
</p></li></ul></div></div><p></p><div><div><p><b>Required Qualifications
</b></p></div><div><ul><li><p>Bachelor&rsquo;s degree in Computer Science , Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
</p></li></ul></div><div><ul><li><p>10&ndash;15+ years of experience in:
</p></li></ul></div><div><ul><li><p>D eep learning model development or deployment experience on CPUs/GPUs/ASICs.
</p></li></ul></div><div><ul><li><p>Inference systems and optimization
</p></li></ul></div><div><ul><li><p>Data center or edge AI platforms
</p></li></ul></div><div><ul><li><p>Strong experience with:
</p></li></ul></div><div><ul><li><p>Model quantization and optimization techniques
</p></li></ul></div><div><ul><li><p>AI model frameworks (e.g., PyTorch , TensorFlow)
</p></li></ul></div><div><ul><li><p>Model deployment pipelines
</p></li></ul></div><div><ul><li><p>Excellent C/C++/Python programming and software design skills, including debugging, and performance analysis.
</p></li></ul></div><div><ul><li><p>Hands on expertise with Linux-based systems, low level software, drivers, and system bring up.
</p></li></ul></div><div><ul><li><p>Proven ability to analyze and optimize model performance in production environments.
</p></li></ul></div><div><ul><li><p>Solid understanding of:
</p></li></ul></div><div><ul><li><p>AI inference hardware constraints
</p></li></ul></div><div><ul><li><p>System level performance bottlenecks
</p></li></ul></div><div><ul><li><p>Strong communication skills and experience in customer facing technical roles.
</p></li></ul></div><div><ul><li><p>Willingness to travel for customer engagements and strategic reviews.<br>
</p></li></ul></div></div><p></p><div><div><p><b>Preferred Qualifications
</b></p></div><div><ul><li><p>Skilled in deploying models on platforms that use hardware accelerators for inference.
</p></li></ul></div><div><ul><li><p>Experienced with managing multi-model workflows and building real-time AI systems, including computer vision, video, and analytics projects.
</p></li></ul></div><div><ul><li><p>Knowledgeable about distributed inference methods and handling large-scale model deployments.
</p></li></ul></div><div><ul><li><p>Proficient in developing and maintaining video processing workflows and using relevant software frameworks.
</p></li></ul></div><div><ul><li><p>Deep understanding of how system-level decisions affect performance in actual deployment environments.
</p></li></ul></div><div><ul><li><p>Capable of simplifying complex technical ideas into straightforward, useful advice for clients.
</p></li></ul></div><div><ul><li><p>Hands-on experience running deep learning models on popular ML frameworks such as PyTorch , TensorFlow, ONNX
</p></li></ul></div><div><ul><li><p>Experience developing software solutions that run in Linux environments with containers and orchestration
</p></li></ul></div><div><ul><li><p>Experience with Source code and configuration management tools, Git knowledge is required.
</p></li></ul></div><div><ul><li><p>Customer-facing experience translating customer requirements into technical solutions (discovery, scoping, success criteria, and execution plans).
</p></li></ul></div><div><ul><li><p>Proven ability to build and deliver technical demos, proofs-of-concept, and reference applications for ML/GenAI workloads.
</p></li></ul></div><div><ul><li><p>Strong technical writing skills to produce customer-ready documentation (getting started guides, deployment runbooks, troubleshooting guides) and deliver partner training sessions.
</p></li></ul></div><div><ul><li><p>Experience driving issue triage and technical escalations with customers, coordinating across product , hardware, and software engineering teams to resolution.
</p></li></ul></div><div><ul><li><p>Excellent stakeholder management and communication skills: present complex technical concepts clearly to both engineering and non-engineering audiences.<br>
</p></li></ul></div></div><p></p><div><p><b>Why Join Qualcomm
</b></p></div><div><p>At Qualcomm, you&rsquo;ll work at the intersection of <b>AI silicon, system architecture, and real </b>‑ <b>world deployment </b>. You will engage directly with strategic customers, influence next ‑ generation AI data center platforms, and help define scalable, power ‑ efficient infrastructure for the AI era. This role provides a unique opportunity to shape both <b>technology direction and customer outcomes </b>, while working with world ‑ class engineering and product teams.
</p><p></p><p><b>What's on Offer
</b></p><p>Apart from working with great people, we offer the below:
</p><ul><li><p>Salary including housing &amp; transport allowance
</p></li><li><p>Stock (RSU's) and performance related bonus
</p></li><li><p>16 weeks fully paid Maternity Leave
</p></li><li><p>6 weeks fully paid Paternity Leave
</p></li><li><p>Employee stock purchase scheme
</p></li><li><p>Child Education Allowance
</p></li><li><p>Relocation and immigration support (if needed)
</p></li><li><p>Life and Medical Insurance
</p></li><li><p>Live+ Well Reimbursement for health and recreational membership fees
</p></li></ul></div><p></p><p><b>Minimum Qualifications:
</b></p><ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Engineering or related work experience.
</li></ul>OR
<br>
Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Software Engineering or related work experience.
<br>
OR
<br>
PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
<br>
<br>
<ul><li>3+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
</li></ul><p></p><p>*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.
</p><p></p><div><p>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).
</p></div><p></p><p>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.
</p><p></p><p><b>To all Staffing and Recruiting Agencies </b>: 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.
</p><p></p><p>If you would like more information about this role, please contact Qualcomm Careers .</p></div>

ML Application Engineer – AI Inference & Model Optimization (Staff/Senior Staff level) - Riyadh, KSA

Datamatics Global Services Ltd

<div><b>Position Title : AI/ML Engineer &ndash; Agentic AI</b><br>
<b>Experience Required: </b>4&ndash;6 Years (Should be open to Travel)<br>
<b>Employment Type : </b>Full-Time - Riyadh - Onsite<br>
<br>
<b>Job Overview</b><br>
We are seeking a highly skilled AI/ML Engineer with hands-on experience in building intelligent AI systems, machine learning models, and Agentic AI solutions. The ideal candidate will have strong expertise in designing, developing, and deploying AI-powered applications leveraging LLMs, autonomous agents, orchestration frameworks, and modern ML techniques.<br>
The role requires a strong engineering mindset, practical AI implementation experience, and the ability to work across the full AI/ML lifecycle from experimentation to production deployment.<br>
<br>
<b>Key Responsibilities</b><ul><li>
Design, develop, and deploy AI/ML solutions for real-world business use cases.</li><li>
Build and optimize <b>Agentic AI systems</b> using LLMs, autonomous workflows, and multi-agent architectures.</li><li>
Develop machine learning models for prediction, classification, recommendation, NLP, and automation tasks.</li><li>
Work with orchestration frameworks such as LangChain, CrewAI, AutoGen, LangGraph, or similar technologies.</li><li>
Integrate AI agents with APIs, databases, enterprise systems, and third-party tools.</li><li>
Fine-tune, evaluate, and optimize Large Language Models (LLMs).</li><li>
Develop Retrieval-Augmented Generation (RAG) pipelines and vector search implementations.</li><li>
Collaborate with data engineers, software developers, and product teams to deliver scalable AI solutions.</li><li>
Perform prompt engineering, model experimentation, and performance optimization.</li><li>
Ensure AI solutions are production-ready, scalable, secure, and cost-efficient.</li><li>
Monitor model performance, drift, and continuous improvement processes.</li><li>
Stay updated with emerging AI, Generative AI, and Agentic AI trends and technologies.</li></ul><b>
Required Skills &amp; Expertise</b><ul><li>
Strong hands-on experience in <b>Machine Learning, Generative AI, and Agentic AI development</b>.</li><li>
Proficiency in Python and AI/ML development frameworks.</li><li>
Experience with:<ul><li>
LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks</li><li>
OpenAI, Anthropic, Gemini, or open-source LLMs</li><li>
RAG architectures and Vector Databases</li><li>
Prompt Engineering &amp; AI workflow automation</li></ul></li><li>
Solid understanding of:<ul><li>
NLP concepts</li><li>
ML algorithms and model evaluation</li><li>
Deep Learning fundamentals</li><li>
AI model deployment and inference optimization</li></ul></li><li>
Experience with ML libraries/frameworks such as:<ul><li>
PyTorch</li><li>
TensorFlow</li><li>
Scikit-learn</li><li>
Hugging Face Transformers</li></ul></li><li>
Experience with cloud platforms such as Azure, AWS, or GCP is preferred.</li><li>
Familiarity with Docker, APIs, CI/CD, and MLOps practices.</li><li>
Strong problem-solving and analytical skills.</li></ul><b>
Preferred Qualifications</b><ul><li>
Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, or related field.</li><li>
Experience working on enterprise AI automation or AI assistant platforms is highly preferred.</li><li>
Exposure to AI governance, evaluation frameworks, and AI observability tools is a plus.</li></ul><br>
<p>
</p><p>tTAmIvfFVv</p></div>

AI/ML Engineer – Agentic AI

SentinelOne

<div><div><h3 class="jobSectionHeader"><b>Our Purpose</b></h3><br>
<p>
At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here.</p>
<h3 class="jobSectionHeader"><b>
About Us</b></h3><br>
<p>
SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters.</p>
<p>
Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity.</p>
<h3 class="jobSectionHeader"><b>
What Are We Looking For?</b></h3>
<p>
We're looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.</p></div><p>
As a <b>Senior Solutions Engineer,</b> you will serve as the strategic technical expert within the field, partnering closely with sales, customers, and ecosystem stakeholders to drive meaningful outcomes.</p>
<p>
You will act as a trusted advisor to enterprise and government clients &mdash; shaping their security strategy, understanding complex environments, and guiding them toward a unified, AI-powered defense with the SentinelOne Singularity Platform. If you thrive at the intersection of deep technical expertise, customer engagement, and business impact, this role is built for you.</p>
<h3 class="jobSectionHeader"><b>
What Will You Do?</b></h3>
<p>
Primary responsibilities include:</p>
<ul>
<li>Partner strategically with the sales organization to qualify and shape opportunities by deeply understanding customer environments, challenges, and business drivers.</li>
<li>Lead high-impact technical engagements &mdash; including deep-dive discussions, advanced product demonstrations, PoVs/PoCs, and architectural reviews &mdash; to showcase the full capabilities of the SentinelOne Singularity Platform.</li>
<li>Serve as a senior subject-matter expert across EDR/XDR, AI Security, Cloud Security, Identity Security, Observability, and SIEM, translating complex concepts into meaningful business and security outcomes.</li>
<li>Act as a trusted advisor to enterprise and government customers, guiding them in designing, validating, and implementing robust, scalable security architectures, and deliver compelling executive-level presentations tailored to customer priorities.</li>
<li>Own and contribute to RFP/RFI processes, channel customer insights back to Product and Engineering teams to influence roadmap direction, and mentor junior and mid-level SEs to drive technical excellence across the wider team.</li>
</ul><h3 class="jobSectionHeader"><b>What Skills and Knowledge Will You Bring?</b></h3>
<p>
Ideal candidates will have:</p>
<ul>
<li>6+ years of hands-on experience in Solutions Engineering or technical pre-sales, with deep expertise in cybersecurity, EDR/XDR, SIEM, observability, and modern security architectures.</li>
<li>Strong technical depth across industry-leading platforms and frameworks in endpoint security, cloud security, identity, logging, and threat detection, including proven experience with AWS, Azure, and GCP.</li>
<li>Exceptional communication, storytelling, and presentation skills, with the ability to articulate complex technical concepts to executives, architects, and practitioners alike.</li>
<li>Demonstrated ability to diagnose challenges in large, complex environments, design scalable outcome-focused solutions, and build long-term trust with enterprise and government customers.</li>
<li>Highly self-driven and organized, with a genuine passion for cybersecurity innovation and AI-driven security, and the ability to manage multiple high-stakes engagements in fast-paced environments.</li>
</ul><h3 class="jobSectionHeader"><b>Why SentinelOne?</b></h3>
<p>
AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.</p>
<p>
We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:</p>
<p><b>
Time Off &amp; Wellbeing</b></p>
<ul>
<li>Competitive leave benefits</li>
<li>Gender-neutral parental leave</li>
</ul>
<p><b>Insurance &amp; Financial Security</b></p>
<ul>
<li>Medical and insurance benefits</li>
<li>Housing, education and transportation allowances</li>
</ul>
<p><b>Work Perks &amp; Flexibility</b></p>
<ul>
<li>Global home office allowance</li>
<li>Mobile phone allowance</li>
</ul><div><p>
SentinelOne is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.</p>
<p>
SentinelOne participates in the E-Verify Program for all U.S. based roles.</p></div></div>

Senior Solutions Engineer

Accor

<div><b>Company Description</b><p><br>
Mӧvenpick Hotel &amp; Residences Riyadh</p><b><br>
Job Description</b><p><br>
The Chief Engineer is responsible for directing, overseeing, and managing all aspects of the hotel&rsquo;s engineering and maintenance operations. This includes the efficient operation of all mechanical, electrical, plumbing (MEP), HVAC, and structural systems, alongside civil works and grounds maintenance. The role ensures full compliance with Accor brand standards, Saudi Arabian local regulations, and strict sustainability protocols while maintaining an exceptional, safe environment for guests and team members.</p><p><b>
Key Responsibilities</b></p><p><b>
1. Operational &amp; Technical Management</b></p><ul><li><p>
Direct day-to-day engineering operations, ensuring all guest rooms, public areas, heart-of-house spaces, and residences are maintained in pristine condition.</p></li><li><p>
Manage and optimize the operation of major plant equipment, including HVAC, chillers, boilers, electrical substations, fire life safety (FLS) systems, and water treatment facilities.</p></li><li><p>
Oversee a robust <b>Preventive Maintenance (PM)</b> program across all equipment and facilities to minimize downtime and extend asset lifespans.</p></li><li><p>
Respond swiftly and effectively to emergency maintenance requests and operational breakdowns.</p></li></ul><p><b>
2. Financial &amp; Asset Management</b></p><ul><li><p>
Formulate, monitor, and manage the Engineering department's annual operating budget (OpEx) and Capital Expenditure (CapEx) plans.</p></li><li><p>
Implement aggressive energy-conservation and waste-management programs to control utility costs without compromising guest comfort.</p></li><li><p>
Oversee contract negotiations and manage relations with third-party vendors, contractors, and service providers, ensuring strict adherence to SLAs.</p></li></ul><p><b>
3. Compliance, Safety &amp; Security</b></p><ul><li><p>
Ensure the property is 100% compliant with Saudi Arabia&rsquo;s local building codes, civil defense regulations, and municipality standards.</p></li><li><p>
Maintain and regularly test all <b>Fire Life Safety (FLS)</b> systems, organizing regular drills and training sessions in coordination with the Risk &amp; Security team.</p></li><li><p>
Drive environmental and sustainability initiatives aligned with Accor&rsquo;s Planet 21 / ESG commitments and local regulatory frameworks (e.g., SFDA or municipal hygiene standards affecting engineering/water quality).</p></li></ul><p><b>
4. Leadership &amp; Culture</b></p><ul><li><p>
Lead, mentor, and develop the engineering team, fostering a high-performance &quot;hotelier&quot; culture focused on attention to detail.</p></li><li><p>
In coordination with the <b>People &amp; Culture</b> department, identify training needs, manage performance evaluations, and actively support the development and integration of Saudi national talent (Saudization initiatives) within the technical team.</p></li><li><p>
Maintain seamless communication and collaboration with other departments, particularly Housekeeping, Front Office, and Food &amp; Beverage, to resolve issues promptly.</p></li></ul><p><b>
Skills &amp; Qualifications</b></p><ul><li><p><b>
Education:</b> Bachelor&rsquo;s degree in Mechanical, Electrical, or Civil Engineering, or an equivalent technical degree. Professional certifications in facilities management or safety are highly preferred.</p></li><li><p><b>
Experience:</b> Minimum of 5&ndash;8 years of experience as a Seasonal Chief Engineer or premium international 5-star hotel or luxury serviced residences. Experience within the GCC (specifically KSA) is a distinct advantage.</p></li><li><p><b>
Technical Skills:</b> Deep knowledge of building management systems (BMS), MEP infrastructure, HVAC, and FLS codes. Proficiency in maintenance management software (e.g., Opera, Maximo, or similar).</p></li><li><p><b>
Language:</b> Fluent in English (written and spoken) is mandatory. Arabic language skills are highly valued.</p></li><li><p><b>
Competencies:</b> Strong leadership capabilities, strategic financial planning, exceptional problem-solving skills under pressure, and a sharp eye for asset preservation.</p></li></ul></div>

Seasonal Chief Engineer

<div><h2 class="jobSectionHeader"><b>Company:
</b></h2>Qualcomm Middle East Information Technology Company LLC
<p></p><h2 class="jobSectionHeader"><b>Job Area:
</b></h2>Engineering Group, Engineering Group &gt; Software Engineering
<p></p><p><b>General Summary:
</b></p><p></p><div><div><p><b>About Us
</b></p></div><div><p>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 intelligent edge devices, next-generation computing platforms, and advanced AI solutions. Qualcomm&rsquo;s leadership in AI, high ‑ performance compute, and connectivity is driving innovation across cloud, edge, and data center environments - delivering scalable, power ‑ efficient platforms that power the next generation of intelligent infrastructure.<br>
</p></div><p></p><div><p><b>About the Role
</b></p></div><div><p>Qualcomm is seeking a <b>Machine Learning Operations &amp; Customer Support Engineer </b>within the Customer Engineering team to support strategic customers deploying AI inference workloads on advanced Qualcomm AI inference accelerator s . These accelerators utilize Qualcomm's expertise in hardware-accelerated AI to deliver high-performance, energy-efficient generative AI and computer vision inference solutions for modern data centers.
</p></div><p></p><div><p>This is a <b>customer-facing, production-critical role </b>focused on ensuring maximum system uptime, reliability, and performance, while resolving customer support cases within defined SLAs/KPIs. The role requires deep expertise across ML inference pipelines, systems troubleshooting , and data center operations, working closely with customers, internal engineering, and product teams.
</p></div><div><p>The i deal candidate will bring a strong foundation in ML model deployment, systems engineering, rack-scale management software, DevOps/ MLOps automation, and cross functional collaboration.<br>
</p></div><p></p><div><p><b>What You&rsquo;ll Do
</b></p></div><div><p><b>Customer Support &amp; SLA Ownership
</b></p></div><div><ul><li>Act as the primary technical escalation point for customer issues related to AI inference workloads
</li></ul></div><div><ul><li>Own end-to-end case management, ensuring resolution within agreed SLAs and KPIs
</li></ul></div><div><ul><li><p>Drive incident response, triage, and root cause analysis (RCA) .
</p></li></ul></div><div><ul><li><p>Provide timely and transparent communication to customers on issue status and resolution
</p></li></ul></div><div><ul><li><p>Maintain high levels of customer satisfaction and service reliability
</p></li></ul></div><p></p><div><p><b>Uptime, Reliability &amp; Operations
</b></p></div><div><ul><li><p>Ensure high availability and uptime of customer AI deployments (rack-scale systems)
</p></li></ul></div><div><ul><li><p>Monitor system health, performance metrics, and workload behavior
</p></li></ul></div></div><div><div><ul><li><p>Implement and manage failover, redundancy, and resiliency mechanisms
</p></li></ul></div><div><ul><li><p>Proactively identify risks and implement preventative actions
</p></li></ul></div><p></p><div><p><b>AI Inference Workload Support
</b></p></div><div><ul><li><p>Support deployment, optimization, and troubleshooting of ML inference pipelines
</p></li></ul></div><div><ul><li><p>Debug issues across model, runtime, system, and hardware layers
</p></li></ul></div><div><ul><li><p>Analyze model performance (latency, throughput, accuracy tradeoffs) in production
</p></li></ul></div><div><ul><li><p>Support frameworks such as PyTorch , TensorFlow, ONNX, and model conversion flows
</p></li></ul></div><div><ul><li><p>Assist in model optimization techniques (quantization, batching, compilation, runtime tuning)
</p></li></ul></div><p></p><div><p><b>System &amp; Infrastructure Engineering
</b></p></div><div><ul><li><p>Support bare-metal and virtualized environments for AI workloads
</p></li></ul></div><div><ul><li><p>Troubleshoot issues across Linux OS, drivers, firmware, and networking stack
</p></li></ul></div><div><ul><li><p>Support deployment and maintenance using Infrastructure as Code ( IaC ) and automation tools
</p></li></ul></div><div><ul><li><p>Work with DCIM tools and monitoring systems for infrastructure visibility
</p></li></ul></div><div><ul><li><p>Coordinate with hardware vendors for accelerator, server, and networking issues
</p></li></ul></div><p></p><div><p><b>Monitoring, Observability &amp; Automation
</b></p></div><div><ul><li><p>Implement and manage monitoring systems (logs, metrics, traces)
</p></li></ul></div><div><ul><li><p>Build dashboards for uptime, SLA adherence, performance, and utilization
</p></li></ul></div><div><ul><li><p>Automate repetitive operational tasks using scripts and workflows
</p></li></ul></div><div><ul><li><p>Establish and enforce runbooks and standard operating procedures (SOPs)
</p></li></ul></div><p></p><div><p><b>Cross-Functional Collaboration
</b></p></div></div><div><div><ul><li><p>Work closely with Customer Engineering, Product, Engineering, and Support teams
</p></li></ul></div><div><ul><li><p>Provide structured feedback to engineering for product improvements and defect resolution
</p></li></ul></div><div><ul><li><p>Support customer onboarding, deployment readiness, and operational handover
</p></li></ul></div><div><ul><li><p>Participate in customer reviews, escalations, and technical deep dives<br>
</p></li></ul></div><p></p><div><p><b>Required Qualifications
</b></p></div><div><ul><li><p>Bachelor&rsquo;s degree in Computer Science , Computer Engineering, Electrical Engineering, or related field
</p></li></ul></div><div><ul><li><p>10&ndash;15+ years of experience in ML operations, systems engineering, or customer support engineering
</p></li></ul></div><div><ul><li><p>Proven experience in customer-facing technical roles with SLA-driven support models
</p></li></ul></div><div><ul><li><p>Strong experience with AI/ML inference workloads in production environments
</p></li></ul></div><div><ul><li><p>Deep understanding of end-to-end ML inference pipelines
</p></li></ul></div><div><ul><li><p>Hands-on experience with Linux systems, system bring-up, drivers, and debugging tools
</p></li></ul></div><div><ul><li><p>Strong understanding of AI accelerator architecture and system bottlenecks
</p></li></ul></div><div><ul><li><p>Experience with model deployment, optimization, and performance tuning
</p></li></ul></div><div><ul><li><p>Experience with data center operations and rack-scale deployments
</p></li></ul></div><div><ul><li><p>Familiarity with bare-metal, virtualization, and containerization technologies (Docker, Kubernetes)
</p></li></ul></div><div><ul><li><p>Knowledge of networking concepts (TCP/IP, RDMA, storage systems)
</p></li></ul></div><div><ul><li><p>Experience with cloud and hybrid environments
</p></li></ul></div><div><ul><li><p>Experience with monitoring/observability tools (Prometheus, Grafana, ELK, etc.)
</p></li></ul></div><div><ul><li><p>Strong skills in incident management, RCA, and production operations
</p></li></ul></div></div><div><div><ul><li><p>Experience defining and tracking SLAs, KPIs, and operational metrics
</p></li></ul></div><div><ul><li><p>Proficiency in Python, Bash, or similar scripting languages
</p></li></ul></div><div><ul><li><p>Experience in automation, DevOps, and MLOps tooling
</p></li></ul></div><div><ul><li><p>Strong problem-solving and diagnostic skills
</p></li></ul></div><div><ul><li><p>Excellent communication and customer engagement skills
</p></li></ul></div><div><ul><li><p>Ability to operate in high-pressure, mission-critical environments
</p></li></ul></div><div><ul><li><p>High attention to detail with a focus on quality, reliability, and accountability
</p></li></ul></div><p></p><div><p><b>Preferred Qualifications
</b></p></div><div><ul><li><p>Experience with Qualcomm Cloud AI or similar AI accelerator platforms
</p></li></ul></div><div><ul><li><p>Experience supporting large-scale AI deployments (LLMs, CV pipelines, generative AI)
</p></li></ul></div><div><ul><li><p>Familiarity with inference runtimes ( TensorRT , ONNX Runtime, custom runtimes)
</p></li></ul></div><div><ul><li><p>Experience with CI/CD pipelines for ML deployment<br>
</p></li></ul></div><p></p><div><p><b>Why Join Qualcomm
</b></p></div><div><p>At Qualcomm, you&rsquo;ll work at the intersection of <b>AI silicon, system architecture, and real </b>‑ <b>world deployment </b>. You will engage directly with strategic customers, influence next ‑ generation AI data center platforms, and help define scalable, power ‑ efficient infrastructure for the AI era. This role provides a unique opportunity to shape both <b>technology direction and customer outcomes </b>, while working with world ‑ class engineering and product teams.
</p><p></p><p><b>What's on Offer
</b></p><p>Apart from working with great people, we offer the below:
</p><ul><li><p>Salary including housing &amp; transport allowance
</p></li><li><p>Stock (RSU's) and performance related bonus
</p></li><li><p>16 weeks fully paid Maternity Leave
</p></li><li><p>6 weeks fully paid Paternity Leave
</p></li><li><p>Employee stock purchase scheme
</p></li><li><p>Child Education Allowance
</p></li><li><p>Relocation and immigration support (if needed)
</p></li><li><p>Life and Medical Insurance
</p></li><li><p>Live+ Well Reimbursement for health and recreational membership fees
</p></li></ul></div></div><p></p><p><b>Minimum Qualifications:
</b></p><ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
</li></ul>OR
<br>
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
<br>
OR
<br>
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
<br>
<br>
<ul><li>2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
</li></ul><p></p><p>*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.
</p><p></p><div><p>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).
</p></div><p></p><p>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.
</p><p></p><p><b>To all Staffing and Recruiting Agencies </b>: 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.
</p><p></p><p>If you would like more information about this role, please contact Qualcomm Careers .</p></div>

ML Operations & Customer Support Engineer, Staff/Senior Staff level - Riyadh, KSA

Adree

<div><p>Adree is looking for a Security Engineer to support our product development and engineering initiatives by leveraging deep application security and analytical expertise to articulate the value of secure, compliant digital solutions. In this role, you will work closely with stakeholders to understand technical requirements and business goals, and clearly demonstrate how enforceable security gates and robust vulnerability lifecycle management can address their needs.</p><p>
You will be responsible for bridging the gap between security compliance and rapid delivery execution, collaborating across teams to operationalize automated security controls throughout the SDLC. By blending secrets management, automated scanning pipelines, and artifact trust mechanisms, you will ensure our digital products are highly secure, resilient, and fully audit-ready.</p><p><b>
Key Responsibilities:</b></p><ul><li>
Engage with clients and stakeholders to gather security requirements and understand their digital transformation and compliance goals</li><li>
Deliver impactful presentations, security dashboards, and reporting frameworks showcasing vulnerability triage, remediation tracking, and pipeline safety metrics</li><li>
Support the engineering and DevOps teams in configuring and tuning Fortify SAST/DAST, establishing clear thresholds, and governing exception workflows</li><li>
Provide technical insights and application security expertise throughout the product lifecycle to automate SSL/TLS certificate renewals using HashiCorp Vault and Cert-Manager in Kubernetes</li><li>
Collaborate with cross-functional teams (including DevOps and QA) to build secure pipelines, manage test environment controls, and enforce software supply chain visibility via SBOM integration</li><li>
Stay current with industry trends, OWASP frameworks, container security concepts, and threat modeling to position solution security effectively</li><li>
Conduct workshops and technical triage sessions internally and with clients to define Quality Gates, vulnerability SLAs, and secure secrets management patterns with SecurEnvoy MFA</li><li>
Participate in Agile development processes and release alignments, producing required compliance evidence, scan outputs, approvals, and comprehensive release evidence packs</li></ul><p></p><b><br>
Requirements</b><p><b><br>
Education</b></p><ul><li>
Bachelor&rsquo;s degree in Computer Science, Cyber Security, Software Engineering, or a related technical field.</li></ul><p><b>
Experience</b></p><ul><li>
4+ years of professional experience in Application Security (AppSec), DevSecOps, or Security Engineering.</li><li>
Proven experience operationalizing enforceable security gates within CI/CD pipelines, preferably using Azure DevOps Server.</li><li>
Demonstrated experience with threat modeling, vulnerability management, and operating within government or highly regulated enterprise sectors is a strong plus.</li></ul><p><b>
Skills &amp; Competencies (Technical &amp; Analytical + Soft)</b></p><ul><li>
Deep proficiency in Secure SDLC principles, OWASP Top 10, container security concepts, and Kubernetes/OpenShift security basics.</li><li>
Strong hands-on experience implementing image signing/verification (Sigstore/Cosign) and artifacts lifecycle security via JFrog Artifactory.</li><li>
Analytical skills to correlate security logs and monitoring alerts with enterprise platforms like AppDynamics, BMC, or Azure Monitoring.</li><li>
Excellent soft skills with an ability to influence without authority, deliver pragmatic risk-based guidance, and handle security escalations calmly.</li><li>
Strong collaboration, structured reporting, and cross-functional engineering alignment.</li></ul><p><b>
Experience (summary)</b></p><ul><li>
Operationalization of automated DevSecOps security gates across CI/CD pipelines</li><li>
Vulnerability lifecycle management including triage, SLA tracking, and remediation</li><li>
Automated software supply chain security (SBOM generation &amp; container image signing)</li><li>
Secrets management integration and automated infrastructure certificate management</li><li>
Application security scanning optimization across SAST and DAST frameworks</li><li>
Regulatory compliance evidence gathering and release package auditing</li></ul><p><b>
Skills &amp; Competencies (summary)</b></p><ul><li>
Azure DevOps Server &amp; JFrog Artifactory secure workflow management</li><li>
Fortify SAST/DAST tuning &amp; exception workflow design</li><li>
HashiCorp Vault secrets management &amp; Cert-Manager infrastructure</li><li>
Container &amp; cluster security principles (Kubernetes / Red Hat OpenShift)</li><li>
Multi-factor authentication access patterns (SecurEnvoy MFA)</li><li>
Stakeholder relationship management &amp; security governance</li><li>
Prioritization, risk-based communication, and teamwork</li><li>
Travel for client-facing activities</li></ul><p></p><p><b>
Job location: HQ</b></p></div>

Security Engineer, Specialist

TAWANTECH

<div><p><b>Job Summary</b></p><p>
We are seeking an AI Software Engineer with hands-on experience in Large Language Models (LLMs) and Generative AI technologies to develop intelligent solutions that enhance customer experience, operational efficiency, and knowledge management within the banking sector.</p><p></p><p><b>
Key Responsibilities</b></p><ul><li>Design, develop, and deploy AI-powered applications leveraging LLMs and Generative AI.</li><li>Build Retrieval-Augmented Generation (RAG) solutions using enterprise banking data.</li><li>Develop intelligent assistants, chatbots, and knowledge management solutions.</li><li>Integrate AI services with banking applications and APIs.</li><li>Fine-tune, evaluate, and optimize LLM performance.</li><li>Ensure compliance with banking security, governance, and regulatory requirements.</li><li>Collaborate with business, data, and technology teams to deliver AI-driven solutions.</li></ul><b><br>
Requirements</b><ul><li><br>
4+ years of software engineering experience.</li><li>Strong Python programming skills.</li><li>Experience with LLMs, Generative AI, and Prompt Engineering.</li><li>Experience with LangChain, LlamaIndex, Vector Databases, and RAG architectures.</li><li>Familiarity with machine learning frameworks and AI deployment practices.</li><li>Experience with cloud platforms (AWS, Azure, GCP) is preferred.</li></ul><p></p><p><b>
Preferred Qualifications</b></p><ul><li>Banking or Financial Services experience.</li><li>Experience developing AI copilots or customer-facing AI solutions.</li><li>Knowledge of AI governance and responsible AI practices.</li></ul></div>

AI Software Engineer / LLM Engineer

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