Senior/Staff Software Engineer, ML Data Infrastructure

Who you are

You have 5+ years of experience in software engineering with a strong focus on machine learning and data infrastructure — you've designed and implemented scalable data pipelines that support complex machine learning models and autonomous systems. Your expertise in Python and familiarity with cloud services like AWS enable you to build robust solutions that handle large volumes of data efficiently.

You possess a deep understanding of data processing frameworks and tools such as Kafka and Docker — you've utilized these technologies to create reliable data ingestion and processing workflows that meet the demands of real-time and batch processing. Your experience with Kubernetes allows you to manage containerized applications effectively, ensuring high availability and scalability.

Your background in machine learning frameworks like TensorFlow and PyTorch is extensive — you've developed and deployed machine learning models that leverage large datasets for training and evaluation, contributing to the advancement of autonomous driving systems. You understand the importance of data quality and have implemented strategies to ensure the integrity and reliability of the data used in model training.

You are a collaborative team player who enjoys working closely with system engineers and data scientists — you thrive in environments where cross-functional collaboration is key to success. Your strong communication skills enable you to articulate complex technical concepts to both technical and non-technical stakeholders, fostering a shared understanding of project goals and challenges.

Desirable

Experience with SQL and database management systems is a plus — you've optimized data storage solutions to accommodate diverse data types and ensure efficient retrieval for analysis. Familiarity with machine learning operations (MLOps) practices will enhance your ability to streamline the deployment and monitoring of machine learning models in production.

What you'll do

In this role, you will design and develop unified, introspectable, large-scale batch and streaming data pipelines that can ingest and process data across a wide range of use cases relevant to evaluation. You will create and implement a storage system capable of accommodating both the large volume and diverse range of evaluation and performance metrics, ensuring that the data infrastructure supports the machine learning lifecycle effectively.

You will collaborate closely with system engineers to validate the autonomous driving system before its deployment — your contributions will be critical in ensuring that the data used for training and evaluation meets the highest standards of quality and relevance. You will also be responsible for monitoring the performance of data pipelines and making necessary adjustments to optimize their efficiency and reliability.

As part of a dynamic team, you will have the opportunity to influence the direction of data infrastructure initiatives and contribute to the overall mission of making autonomy accessible to all. You will stay abreast of industry trends and emerging technologies, continuously seeking ways to enhance the capabilities of the data infrastructure to support innovative applications in autonomous driving.

What we offer

Nuro offers a collaborative and inclusive workplace that fosters psychological safety for all employees. You will be part of a team that is dedicated to pushing the boundaries of self-driving technology, working on projects that have a meaningful impact on the future of mobility. We encourage you to apply even if your experience doesn't match every requirement — your unique perspective and skills could be a valuable addition to our team. Competitive compensation and benefits are provided, reflecting our commitment to attracting and retaining top talent in the industry.