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

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 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.

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 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.

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