Full Stack Machine Learning Engineer - Data Centre AI Engineering

About Qualcomm

Qualcomm is a global leader driving intelligent connectivity, powering devices and technologies such as 5G-enabled smartphones, smart vehicles, and connected cities. With innovations in AI and 5G, Qualcomm supports smart factories and diverse industries worldwide, delivering impactful technologies used daily by billions.

Expanding its footprint in Riyadh, Saudi Arabia, Qualcomm is enhancing its regional infrastructure and data centre capabilities to support AI, cloud, and advanced connectivity, aligned with Saudi Vision 2030's digital transformation goals.

Role Overview

This position is for a Full Stack Machine Learning Engineer who will contribute to the development and engineering of AI solutions within Qualcomm’s AI Inference Suite and large-scale data centre environments. The engineer will design, implement, and maintain end-to-end AI services, agentic workflows, fine-tuning pipelines, and infrastructure automation for scalable AI workloads, ensuring robust lifecycle management, orchestration, and monitoring.

Key Responsibilities

• Develop and optimize APIs to efficiently serve AI inference models and maximize hardware utilization.
• Create intelligent agent workflows and retrieval-augmented generation pipelines utilizing frameworks like LangChain and crew.ai.
• Manage machine learning model lifecycles including dataset ingestion, orchestration, evaluation, deployment, and fine-tuning.
• Integrate and optimize various large language model runtimes such as vLLM, Dynamo, and llm-d.
• Contribute to SDKs and toolchains across multiple languages including Python, TypeScript, Java, and Rust, along with CLI tools and reference applications.
• Design and maintain AI cluster management solutions supporting provisioning, orchestration, and monitoring of infrastructure.
• Implement telemetry and observability integrations through Redfish/IPMI protocols and Prometheus/OpenTelemetry tools.
• Automate infrastructure deployments using tools like MAAS, Terraform, Ansible for both bare-metal and containerized environments.
• Enable Kubernetes and Helm orchestration for inference clusters supporting multi-tenant setups.
• Develop dashboards to monitor rack health, inventory levels, and service-level agreement compliance.
• Stay informed on emerging Generative AI trends, orchestration at rack scale, and best practices in data centre operations.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related disciplines.
• At least 5 years in software engineering with a minimum of 3 years focused on machine learning or high-performance computing domains.
• Proficient in Python, Rust or Go, and TypeScript with strong foundations in software engineering principles.
• Solid understanding of data structures, algorithms, and distributed/high-performance computing systems.
• Hands-on expertise with Kubernetes, Helm, Prometheus, OpenTelemetry, Ansible, and Terraform.
• Experience working with LLM runtimes and agent-based frameworks as well as rack-scale system orchestration.

Preferred Qualifications

• Master’s degree in Computer Science, Machine Learning, or closely related fields.
• Experience in developing AI inference and fine-tuning pipelines alongside agentic workflow systems.
• Understanding of data centre resource management, out-of-band management protocols (Redfish/IPMI), and cloud tools such as MAAS and OpenStack.
• Familiarity with advanced data centre networking technologies including RoCE, RDMA, and NVLink.
• Contributions towards improving inference and Generative AI model efficiencies.

Benefits and Compensation

• Competitive salary package including housing and transportation allowances.
• Eligible for stock options (RSUs) and performance bonuses.
• Generous family leave policies: 16 weeks paid maternity, 6 weeks paid paternity leave.
• Employee stock purchase plan and child education allowances.
• Assistance with relocation and immigration if required.
• Comprehensive life and medical insurance coverage.
• Reimbursement programs supporting health and wellness memberships.

Additional Information

Applicants should have at least a Bachelor's degree coupled with 2+ years relevant software engineering experience, or a Master’s describing 1+ year experience, or a PhD in related fields alongside relevant programming experience in languages such as C, C++, Java, or Python.

Qualcomm values inclusivity and equal opportunity employment. Reasonable accommodations are available for candidates with disabilities throughout the recruitment process. Qualcomm expects employees to comply with company policies and uphold confidentiality of proprietary information.

Agency submissions are not accepted; only direct individual applications will be considered.