ML Platform Software Engineer - Qualcomm, flexible on location anywhere in Europe
Indexed description
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.
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.
- 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.
- 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).
- 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.
- 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.
- 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 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.
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