1 day ago
Base Salary
$135k - $203k/yr
Responsibilities
- Identify and prioritize high-impact machine learning use cases for modem and wireless systems.
- Design, develop, train, evaluate, and deploy ML and deep learning models using time-series forecasting, sequence modeling, and modern architectures.
- Build automated end-to-end ML pipelines covering data ingestion, feature generation, training, evaluation, and deployment.
- Design and maintain MLOps infrastructure for reproducible experimentation, model versioning, automation, and scalable use-case onboarding.
- Optimize and deploy ML models for on-device modem targets with strict latency, memory, and compute constraints.
- Implement model health monitoring, KPI regression tracking, and automated data-drift, concept-drift, and performance detection.
- Collaborate with modem, systems, software, test, and platform teams on production rollout and ongoing model performance.
- Design and implement ETL, data platform, observability, and governance pipelines across on-premises and cloud environments.
- Build and manage ML data platforms using cloud services, containers, streaming systems, data platforms, and observability tools.
Requirements
- Bachelor’s degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field plus 2+ years of relevant experience; alternatively, a master’s degree plus 1+ year of relevant experience or a PhD in a related field.
- Bachelor’s degree with at least 1 year of relevant experience or a master’s degree.
- Strong hands-on programming experience in Python and/or C/C++.
- Foundations in machine learning algorithms, probability, statistics, and software engineering principles.
- Experience with deep learning architectures such as CNNs, RNNs, GRUs, LSTMs, Transformers, and related sequence models.
- Proficiency with PyTorch, TensorFlow, or Keras.
- Experience building production-grade ML pipelines for large-scale structured and unstructured datasets.
- Experience with MLOps, experiment tracking, model lifecycle management, ML CI/CD, and cloud/on-device co-development.
- Experience with data drift, concept drift, KPI-based model monitoring, and production performance management.
- Strong software engineering, object-oriented design, debugging, and real-time execution skills.
- Exposure to on-device ML deployment, quantization, and neural network optimization tools.
- Familiarity with AWS SageMaker, Docker/Kubernetes, and automation or orchestration tools.
Benefits
- Competitive annual discretionary bonus program.
- Opportunity for annual RSU grants.
- Competitive benefits package supporting employees at work, at home, and at play.
- The posting provides US benefits details through a linked benefits page.
Tech Stack
Apache KafkaApache SparkAWSCC++DatabricksDatadogDockerGrafanaKerasKubernetesPostgreSQLPrometheusPythonPyTorchRabbitMQSplunkSQLTensorFlow
Categories
About Qualcomm
Qualcomm is a public semiconductor company headquartered in San Diego, founded in 1985, that designs and sells wireless chipsets and platforms for mobile devices, automotive, IoT, and networking, notably the Snapdragon application processors and 5G modems. It also licenses a large portfolio of cellular patents to device makers, generating revenue alongside chip sales; its technology underpins many Android smartphones and emerging automotive and edge-compute systems, and it trades on NASDAQ as QCOM.