ML and Data Ops Intern at Mercedes-Benz… · San Jose

Summary: Mercedes-Benz Research & Development North America is committed to delivering world-class automotive technologies. The ML and Data Ops Intern will enhance ML/Analytics workflows and help transform experimental data science workflows into scalable, production-ready systems. Responsibilities: - Streamline and productionize data science workflows by refactoring ad hoc code into scalable, maintainable ML pipelines and shared libraries - Continuously evaluate the latest packages and frameworks in the ML ecosystem - Enhance error detection and monitoring capabilities for training pipelines - Improve observability by adding robust error handling, logging, and monitoring across data and training pipelines - Work in an Agile/Scrum environment to deliver high quality software with a measurable customer value - Assist in research topics through multiple phases related to automotive machine learning solutions: experimentation and validation, proof of concept, tuning and constraint adjustment, and testing strategies - Provide support and insight to development teams responsible for implementation of machine learning techniques in native head unit environment - Present and demo research topics to Mercedes-Benz internal groups Required Qualifications: - Master's or higher degree, in DS/CS/CE/EE, Math, Statistics, or related field - Strong programming and software development skills in Python, SQL, and Git - Hands-on experience with implementation, analysis and updating machine learning and AI algorithms - Experience designing dashboards for system analysis and data insights - Good understanding of Machine Learning fundamentals - Strong instincts for efficiency and optimization, with self-motivation to work with colleagues such that only high-quality products reach customers' hands - Ability to collaborate effectively and pro-actively in cross functional development teams - Excellent communication, especially written, and organizational skills Preferred Qualifications: - Hands-on experience with cloud MLOPs offerings (AWS SageMaker, Databricks, etc.) - Experience with distributed cloud computing platforms, particularly Kubernetes or the Hadoop/Spark ecosystem - Experience building and optimizing CICD pipelines - Experience working with cloud data processing technologies - Familiar with object-oriented programming - Familiar with end-to-end development of ML models (data processing, feature stores, training, and deployment) for predictive ML and GenAI Required Skills: Python, SQL, Git, Machine Learning, Machine Learning algorithms, Dashboard design, Cloud MLOps, AWS SageMaker, Databricks, Distributed cloud computing, Kubernetes, Hadoop, Spark, CI/CD pipelines, Cloud data processing, Object-oriented programming, ML model development Benefits: PTO, Sick Time, Medical, dental, and vision insurance for employees and their families, 401(k) with employer match, Up to 15 company-paid holidays, Paid time off (flexible time off for salaried employees), sick time, and parental leave, Tuition assistance program, Wellness/Fitness reimbursement programs