Job Description
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Company Overview
A leading global technology and mobility organization is expanding its autonomous technology ecosystem through AV Labs. The team brings together multidisciplinary experts to transform real-world driving operations into high-quality data that can support autonomous technology partners.
The initiative focuses on addressing one of the most challenging areas in autonomous driving: unlocking rare, real-world, long-tail driving data. By leveraging large-scale driving data and advanced artificial intelligence, the organization is developing technologies that can provide deeper insights into complex driving scenarios and accelerate the development and evaluation of autonomous systems.
As a Senior Engineering Manager, AV Labs, the successful candidate will lead a highly specialized team of machine learning engineers and applied researchers focused on AI models and behavioral causality. The role will guide the development of advanced foundation models capable of interpreting complex urban edge cases and adding rich semantic understanding to large-scale driving datasets.
The engineering leader will help drive the technical roadmap behind an L4 data and evaluation platform, enabling autonomous technology partners to extract meaningful insights from extensive real-world driving data.
Key Responsibilities
- Build, manage, and mentor a high-performing engineering team consisting of machine learning experts, AI modelers, and data scientists.
- Foster a culture of rigorous scientific experimentation, high-velocity execution, collaboration, and engineering excellence.
- Lead the development and execution of advanced autonomy algorithms and AI foundation models.
- Guide the team in extracting high-fidelity semantic information from multi-modal sensor data to enrich large-scale autonomous driving datasets.
- Collaborate with technical leadership to establish foundational architectural decisions and long-term engineering strategies.
- Maintain high standards for system quality, reliability, and performance.
- Ensure deployed systems are optimized for low-latency processing of large-scale datasets.
- Partner with engineering directors, principal engineers, product managers, and infrastructure teams to align machine learning initiatives with broader business objectives.
- Drive seamless deployment and scaling of machine learning systems across complex data and infrastructure environments.
- Translate complex technical challenges into clear engineering strategies and execution plans.
Basic Qualifications
- 8+ years of software engineering experience in applied machine learning, AI modeling, or autonomous systems.
- 3+ years of experience managing engineering teams, with a demonstrated history of leading high-performing ML or AI organizations.
- Proven experience delivering complex, large-scale AI models or machine learning pipelines from conception through production.
- Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field.
- Deep expertise in modern AI and machine learning frameworks such as PyTorch and TensorFlow.
- Strong experience working in Python and Linux environments.
Preferred Qualifications
- Advanced degree, such as an MS or PhD, in Robotics, Machine Learning, Computer Vision, or a related field.
- Deep technical understanding of AI foundation models, multi-modal perception, and causal behavior modeling.
- Experience within the autonomous vehicle industry, particularly in offline evaluation, third-party data understanding, or autonomous data mining rather than embedded on-vehicle execution.
- Strong background leading teams that develop models capable of processing, structuring, and querying massive datasets.
- Experience building advanced scene representation systems using large-scale autonomous driving data.
- Excellent communication skills with the ability to translate complex technical concepts into strategic roadmaps for cross-functional stakeholders.
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