Key skills
Machine LearningPythonSQLData TransformationStatistical AnalysisFeature EngineeringMLOps ToolsCloud ML PlatformsGenerative AICollaboration SkillsAIMLLLMOpenAIPyTorchTensorFlowscikit-learnHugging FaceMLOpsMLflowKubeflowAnalyticsAWSAzureKubernetesDockerSageMakerVertex AICommunicationCollaboration
About this role
Cisco is a leading technology company focused on revolutionizing data and infrastructure in the AI era. They are seeking a Data Scientist/Software Engineer to develop software leveraging AI and machine learning techniques to enhance operational efficiency and support innovation across their platforms.
Responsibilities:
- Design, build, and deploy ML models using production test data to predict optical module performance and identify potential failures before they occur. Apply rigorous statistical methods to validate model performance
- Extract complex datasets from production databases using SQL queries and manage the transformation of that data into a format ready for ML model training
- Perform data hygiene, normalization, and feature engineering on manufacturing data to ensure high-quality inputs for ML training
- Implement LLM-based solutions to analyze and summarize complex manufacturing line performance statistics. Develop automated tools that assist project planning personnel to make key supply chain decisions
- Work closely with hardware, product, and project engineering teams to understand the optical module production process and ensure solutions meet defined technical requirements and deliver tangible business impact
- Stay current with AI/ML developments and integrate relevant advancements into ongoing projects and technical plans
Requirements:
- Bachelors + 7 years of related experience, or Masters + 4 years of related experience, or PhD + 1 year of related experience
- 3+ years of experience developing and deploying ML models
- Proficient in Python and at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience with LLMs and Generative AI (e.g., Hugging Face, OpenAI APIs)
- Experience with SQL and data transformation
- Up to date on the latest AI/ML trends (e.g., Foundation Models, Diffusion Models, AutoML)
- Experience in data cleaning, normalization, and feature engineering
- Working knowledge of statistical analysis and model validation
- Strong collaboration and communication skills
- Familiarity with MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes)
- Experience with cloud ML platforms (AWS SageMaker, Google Vertex AI, Azure ML)
- Background with manufacturing, optical hardware, or IoT datasets
- Experience with automated analytics/reporting tools