Company: Qualcomm Europe, Inc. Italy Branch Office Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: We are seeking an exceptional Staff Software Engineer to join our ML Platform team. This role is ideal for a highly technical individual contributor who combines deep hands-on expertise with the ability to lead and drive complex projects independently. You will design, build, and optimize large-scale ML and data infrastructure across on-premises NVIDIA DGX clusters and AWS Cloud, enabling advanced training pipelines, robust data workflows, and production-ready ML solutions. Beyond infrastructure, this position requires strong software engineering fundamentals. You will be expected to write high-quality, production-grade code and master common programming languages. The ideal candidate is passionate about building scalable systems and can balance platform engineering with solid software development practices. 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. Key Responsibilities - Architect and develop core components of the ML platform and data infrastructure for training, inference, and large-scale data processing. - Design and implement scalable solutions for GPU clusters and distributed data pipelines on-prem and in AWS. - Lead project workstreams, ensuring timely delivery and alignment with platform roadmap; operate independently and drive outcomes end-to-end. - Build and optimize data pipelines for ingestion, transformation, storage, and retrieval supporting ML workflows (batch and streaming). - Write clean, efficient, and maintainable code (services, operators, automation, tooling) in multiple programming languages. - Collaborate with data science and engineering teams to integrate ML and data workflows seamlessly (feature stores, model registries, artifact stores). - Implement CI/CD for ML and data workflows using Argo Workflows, ArgoCD, GitHub Actions; champion testability and reproducibility. - Maintain observability (Prometheus, Grafana) and logging (AWS CloudWatch, ELK/Opensearch); drive SLOs, tracing, and cost-awareness. - Operate AWS services (EKS, EC2, VPC, IAM, S3, EFS, Batch) across hybrid environments; contribute to security and compliance controls. - Continuously improve platform reliability, performance (GPU utilization, throughput), and developer experience; stay current on modern MLOps/Data engineering practices. Minimum Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. - 8+ years of software engineering experience, including: - Strong proficiency in Python and at least one of Go, C++, Rust, Bash. - Solid grasp of data structures, algorithms, concurrency, networking, and distributed systems. - Experience with Kubernetes, Helm, Argo Workflows, ArgoCD, Docker. - Ability to pass coding assessments demonstrating problem-solving and clean code practices. - Exposure to AWS (EKS, EC2, VPC, IAM, S3, EFS, Batch) and CI/CD automation. - (Nice-to-have but not required) Hands-on experience with GPU clusters and ML frameworks (TensorFlow, PyTorch). Preferred Qualifications - Proven experience building large-scale data pipelines (batch/streaming), data orchestration, and storage patterns (S3, EFS, parquet/ORC). - Familiarity with observability stacks (Prometheus/Grafana), ELK/Opensearch, and CloudWatch. - Knowledge of ML optimization techniques, GPU memory management, and model deployment at scale. - Experience with security and compliance for ML/data platforms (IAM, policies, isolation). - Prior contributions to platform services (custom controllers/operators, plugins) and developer tooling. - Ability to mentor and influence technical direction while remaining hands-on. What We’re Looking For - A hands-on technical leader who thrives on solving complex, system-level problems and can execute independently. - Excellent communication, cross-functional collaboration, and pragmatic delivery focus. - Passion for building robust, scalable platforms that accelerate ML and data innovation. We will also consider passionate, strong software engineers with excellent fundamentals, even if they lack specific experience in ML platforms or data pipelines. If you demonstrate mastery in core programming, distributed systems, and problem-solving, we’ll support your ramp-up on our stack. *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. To all Staffing and Recruiting Agencies: 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. If you would like more information about this role, please contact Qualcomm Careers.

• Define and own the platform architecture elements that enable our AI systems to run reliably inside sensitive customer environments • Design the BYOC deployment model for Archie across customer environments • Build and own Kubernetes-based infrastructure that runs reliably across multiple clouds and customer setups • Create deployment tooling using Helm, GitOps, or similar approaches to make installation and operations repeatable • Implement secure and reliable update mechanisms that work even in restricted or locked-down network environments • Work closely with product, research, and forward-deployed engineers to translate requirements into platform capabilities • Debug and improve production deployments, identifying bottlenecks in performance, reliability, or operability • Establish observability, monitoring, and debugging patterns that give us visibility into distributed systems we don’t fully control

• Design, implement, and operate a unified MLOps platform • Develop reusable CI/CD pipelines for model packaging and testing • Build observability stacks to track performance • Create self-service tooling for data science teams • Collaborate with research engineers to translate prototypes into production services • Drive performance optimization and champion best practices

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Platform Engineer Job Overview Support and assist in the design, architecture, implementation, security, and ongoing support of large-scale, multi-site, multi-vendor MPLS network environments. Key Responsibilities Lead and implement network infrastructure projects, from design through deployment. Develop detailed requirements for upgrading and re-architecting corporate and Mastercard network environments to support new technologies, business growth, and evolving requirements. Troubleshoot and resolve network communication and operational issues impacting customer access and global backbone performance. Participate in telecommunications and network transformation initiatives. Research, evaluate, and develop innovative unified networking solutions. Support assigned regional projects, including planning, scheduling, cost control, resource coordination, and implementation. Provide vendor management support, including coordination and technical oversight. Education Bachelor's degree in Computer Science, Engineering, Mathematics, or an equivalent combination of education and experience. Knowledge & Experience 3-5 years of overall IT experience, with strong focus on: LAN/WAN networking Firewalls and perimeter security Wireless networking Security and encryption technologies Switching, Spine-Leaf architecture, Routing including BGP, MP-BGP, MPLS, and Traffic Engineering Strong experience with TCP/IP protocol communications. Broad knowledge of Cisco product portfolio. Working knowledge of project management methodologies and best practices. Hands-on experience with network diagnostics and protocols, including: BGP SDWAN VPN SSH MPLS Skills & Abilities Strong verbal and written communication skills. Self-starter with strong listening and collaboration skills. Ability to mentor junior engineers and provide technical leadership. Capable of working with limited supervision; work may be reviewed for strategic alignment and direction. Demonstrates sound judgment in technical and operational decision-making. Work Conditions Supports a 24x7 global network environment. May require occasional travel. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.