وظيفة مهندس عمليات ML ودعم العملاء لدى كوالكوم في الرياض

Company

Qualcomm Middle East Information Technology Company LLC

Job Area

Engineering Group, Engineering Group > Software 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 intelligent edge devices, next-generation computing platforms, and advanced AI solutions. Qualcomm’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.

About The Role

Qualcomm is seeking a Machine Learning Operations & Customer Support Engineer within the Customer Engineering team to support strategic customers deploying AI inference workloads on advanced Qualcomm AI inference accelerators. 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.

This is a customer-facing, production-critical role 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.

The ideal candidate will bring a strong foundation in ML model deployment, systems engineering, rack-scale management software, DevOps/MLOps automation, and cross functional collaboration.

What You’ll Do

Customer Support & SLA Ownership

• Act as the primary technical escalation point for customer issues related to AI inference workloads
• Own end-to-end case management, ensuring resolution within agreed SLAs and KPIs
• Drive incident response, triage, and root cause analysis (RCA).
• Provide timely and transparent communication to customers on issue status and resolution
• Maintain high levels of customer satisfaction and service reliability
  
  
  

Uptime, Reliability & Operations

• Ensure high availability and uptime of customer AI deployments (rack-scale systems)
• Monitor system health, performance metrics, and workload behavior
• Implement and manage failover, redundancy, and resiliency mechanisms
• Proactively identify risks and implement preventative actions
  
  
  

AI Inference Workload Support

• Support deployment, optimization, and troubleshooting of ML inference pipelines
• Debug issues across model, runtime, system, and hardware layers
• Analyze model performance (latency, throughput, accuracy tradeoffs) in production
• Support frameworks such as PyTorch, TensorFlow, ONNX, and model conversion flows
• Assist in model optimization techniques (quantization, batching, compilation, runtime tuning)
  
  
  

System & Infrastructure Engineering

• Support bare-metal and virtualized environments for AI workloads
• Troubleshoot issues across Linux OS, drivers, firmware, and networking stack
• Support deployment and maintenance using Infrastructure as Code (IaC) and automation tools
• Work with DCIM tools and monitoring systems for infrastructure visibility
• Coordinate with hardware vendors for accelerator, server, and networking issues
  
  
  

Monitoring, Observability & Automation

• Implement and manage monitoring systems (logs, metrics, traces)
• Build dashboards for uptime, SLA adherence, performance, and utilization
• Automate repetitive operational tasks using scripts and workflows
• Establish and enforce runbooks and standard operating procedures (SOPs)
  
  
  

Cross-Functional Collaboration

• Work closely with Customer Engineering, Product, Engineering, and Support teams
• Provide structured feedback to engineering for product improvements and defect resolution
• Support customer onboarding, deployment readiness, and operational handover
• Participate in customer reviews, escalations, and technical deep dives
  
  
  

Required Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field
• 10-15+ years of experience in ML operations, systems engineering, or customer support engineering
• Proven experience in customer-facing technical roles with SLA-driven support models
• Strong experience with AI/ML inference workloads in production environments
• Deep understanding of end-to-end ML inference pipelines
• Hands-on experience with Linux systems, system bring-up, drivers, and debugging tools
• Strong understanding of AI accelerator architecture and system bottlenecks
• Experience with model deployment, optimization, and performance tuning
• Experience with data center operations and rack-scale deployments
• Familiarity with bare-metal, virtualization, and containerization technologies (Docker, Kubernetes)
• Knowledge of networking concepts (TCP/IP, RDMA, storage systems)
• Experience with cloud and hybrid environments
• Experience with monitoring/observability tools (Prometheus, Grafana, ELK, etc.)
• Strong skills in incident management, RCA, and production operations
• Experience defining and tracking SLAs, KPIs, and operational metrics
• Proficiency in Python, Bash, or similar scripting languages
• Experience in automation, DevOps, and MLOps tooling
• Strong problem-solving and diagnostic skills
• Excellent communication and customer engagement skills
• Ability to operate in high-pressure, mission-critical environments
• High attention to detail with a focus on quality, reliability, and accountability
  
  
  

Preferred Qualifications

• Experience with Qualcomm Cloud AI or similar AI accelerator platforms
• Experience supporting large-scale AI deployments (LLMs, CV pipelines, generative AI)
• Familiarity with inference runtimes (TensorRT, ONNX Runtime, custom runtimes)
• Experience with CI/CD pipelines for ML deployment
  
  
  

Why Join Qualcomm

At Qualcomm, you’ll work at the intersection of AI silicon, system architecture, and real‑world deployment. 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 technology direction and customer outcomes, while working with world‑class engineering and product teams.

What's On Offer

Apart from working with great people, we offer the below:

• Salary including housing & transport allowance
• Stock (RSU's) and performance related bonus
• 16 weeks fully paid Maternity Leave
• 6 weeks fully paid Paternity Leave
• Employee stock purchase scheme
• Child Education Allowance
• Relocation and immigration support (if needed)
• Life and Medical Insurance
• Live+ Well Reimbursement for health and recreational membership fees
  
  
  

Minimum Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
  
  
  

OR

Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.

OR

PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.

• 2+ years of 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 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).

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