Engineering Manager - Data Ingest & Analysis (Model Dev Platform)
About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us-we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! The Role
Wayve's efforts to develop our autonomous-driving AI starts with the Data Ingest & Analysis team. As its Engineering Manager, you will lead a multidisciplinary group that moves and processes hundreds of petabytes of multimodal driving data-the fuel that trains our end-to-end driving model. Without fast, reliable, and scaled access to driving data, the model cannot learn. Your leadership ensures every training job starts with the right bytes at the right time. Success in this role will have a far-reaching impact, ensuring that Wayve's has access to the data needed to train our AI model.
Challenges You Will Own The Data Ingest & Analysis team own the very first step on Wayve's process of developing its autonomous driving software: the collect, transformation, and analysis of the hundreds of petabytes of driving data used to train our AI to drive vehicles. As the Engineering Manager of this team, you will:
- Team Leadership and Strategic Oversight
- Build and lead a team of data and platform engineers.
- Define and execute the team's roadmap in collaboration with stakeholders from the AI and Vehicle Software organizations.
- Set clear objectives, foster collaboration, and ensure timely delivery of projects.
- Manage and optimize large-scale Spark-based map-reduce data processing pipelines.
- Oversee large scale transcoding and processing workflows to ensure data is ready for AI training.
- Enable the collection of driving data from a large number of both internal and third-party data sources
- Normalize collected data to a consistent schema as needed by Wayve's AI training process
- Leverage work scheduling tools like Flyte to orchestrate multi-faceted data process workflow
- Build and leverage operational observability to understand status of reliable operations
- Set up processes to enable 24/7 reliable operations of workflow
- Technical Mentorship and Talent Development
- Recruit, mentor, and grow your team, cultivating technical excellence.
- Identify skill gaps and facilitate training to meet the evolving needs of the team.
- Proven Leadership: Strong experience in software engineering with experience managing teams focused on data or platform engineering.
- Technical Expertise: Hands-on experience with building ETL workflows in Apache Spark or inferencing workflows orchestrated by Flyte, or comparable technologies
- Experience in Large Scale Data Operations: Demonstrated ability to deliver software solutions that enable collection and processing of petabytes of data
- Strategic Acumen: Proven ability to define, negotiate, and execute technical roadmaps.
- Collaborative Abilities: Exceptional communication skills to effectively liaise with AI developers, infrastructure engineers, and other stakeholders.
- Talent Development: Strong ability to identify, recruit, mentor, develop, and retain top talent
- Educational Background: A degree in Computer Science, Electrical Engineering, or a related field.
- Data Warehouse / Datalake Management: Experience with organising petabyte-scale data sets for use by a wide variety of users.
- Heterogeneous Data Processing: Experience combining Apache Spark with other data processing technologies to produce a multi-faceted workflow for normalizing, labeling, and analyzing data.
- Educational Excellence: A Master's degree or higher in Computer Science, Electrical Engineering, or a related discipline.
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