Full Stack Machine Learning Engineer - Data Centre AI Engineering

About Qualcomm and the Role

Qualcomm is at the forefront of enabling intelligent connectivity across devices and industries worldwide, powering innovations in 5G, AI, and smart infrastructure. As part of its expansion in Riyadh, Saudi Arabia, Qualcomm is hiring Data Centre Engineers to support its growing infrastructure aligned with the Kingdom's Vision 2030 digital transformation.

This position is for a Full Stack Machine Learning Engineer who will connect AI solution development with AI platform engineering, focusing on Qualcomm's AI Inference Suite and large-scale data center deployments. The role involves creating end-to-end AI services, intelligent workflow designs, lifecycle automation, and observability for advanced data center environments.

Key Responsibilities

• Develop and enhance API layers tailored for AI inference, optimizing for hardware and model performance.
• Create intelligent agent workflows and retrieval-augmented generation pipelines using tools like LangChain and crew.ai.
• Manage production workflows for bring-your-own-model and fine-tuning, including dataset processing, orchestration, evaluation, and deployment stages.
• Integrate with various large language model runtimes such as vLLM, Dynamo, and llm-d, applying inference optimization methods.
• Contribute to AI Inference Suite SDKs (Python, TypeScript, Java, Rust), command line tools, and reference implementations.
• Design and oversee AI cluster management software focusing on provisioning, orchestration, and health monitoring.
• Implement telemetry and observability using both out-of-band management protocols like Redfish/IPMI and in-band telemetry tools such as Prometheus and OpenTelemetry.
• Automate infrastructure deployments using tools like MAAS, Terraform, and Ansible for bare-metal and containerized setups.
• Facilitate Kubernetes and Helm orchestration for inference clusters supporting multi-tenancy.
• Create dashboards to monitor rack health, inventory, and compliance with service-level agreements.
• Keep abreast of innovations in Generative AI, rack-scale AI orchestration, and industry best practices for data centers.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related discipline.
• Minimum of 5 years in software engineering, including at least 3 years in machine learning or high-performance computing settings.
• Proficiency in programming with Python, Rust or Go, and TypeScript, and strong foundational software development skills.
• In-depth knowledge of data structures and algorithms applicable to distributed systems and HPC environments.
• Experience with Kubernetes, Helm, Prometheus/OpenTelemetry, and infrastructure automation tools like Ansible and Terraform.
• Hands-on familiarity with large language model runtimes, agent frameworks, and orchestration at rack scale.

Preferred Qualifications

• Advanced degree (Master's or PhD) in Computer Science, Machine Learning or related fields.
• Practical experience building inference and fine-tuning pipelines plus agentic workflows.
• Knowledge of data centre resource lifecycle management, including protocols such as Redfish/IPMI, MAAS, and OpenStack.
• Understanding of scale-up networking technologies including RoCE, RDMA, and NVLink.
• Experience contributing to performance optimizations of inference and generative AI models.

Benefits and Additional Information

• Competitive salary including housing and transportation allowances.
• Equity through restricted stock units (RSUs) and performance-based bonuses.
• Generous parental leave: 16 weeks maternity and 6 weeks paternity, fully paid.
• Employee stock purchase programs.
• Child education allowances, relocation and immigration support if necessary.
• Comprehensive life and medical insurance coverage.
• Reimbursement of health and recreational memberships under the Live+ Well initiative.

Eligibility and Equal Opportunity

Applicants with a Bachelor’s degree plus 2 or more years software engineering experience, or Master’s degree plus 1 or more year experience, or PhD in relevant disciplines with demonstrated programming skills meet eligibility criteria. Qualcomm is committed to equitable hiring and workplace accessibility, including accommodations for applicants with disabilities.