Inference Platform Technical Lead at Wayve

Sunnyvale, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, AutomotiveIndustries

Requirements

The ideal candidate will have a strong background in machine learning infrastructure, with expertise in job scheduling, resource efficiency, and platform reliability. Proven experience in leading the development and evolution of high-performance GPU inference infrastructure, including architecture, design, and implementation, is essential. Familiarity with orchestration frameworks like Flyte and a deep understanding of observability, monitoring, and alerting systems are required. The candidate should also possess strong leadership skills, with experience in mentoring and developing engineering teams, and a proactive approach to anticipating and integrating advances in the AI landscape.

Responsibilities

The Inference Platform Technical Lead will define and drive the technical roadmap for the inference platform, leading the architecture, design, and implementation of scalable inference solutions. Responsibilities include developing and optimizing large-scale GPU inference infrastructure for high availability and resource utilization, advancing smart scheduling and multi-model inference pipelines, and ensuring seamless integration with orchestration frameworks. The role also involves implementing robust observability and monitoring systems, collaborating with SRE teams on automation and incident response, and mentoring team members to foster technical excellence and continuous improvement.

Skills

Machine Learning

Inference

GPU

Job Scheduling

Resource Efficiency

Platform Reliability

Technical Strategy

ML Models

Wayve

Develops autonomous vehicle technology using AI

About Wayve

Wayve.ai develops self-driving technology known as AV2.0, which focuses on creating a smarter and safer approach to autonomous vehicles. Their technology uses embodied AI software that allows vehicles to learn from their experiences and adapt to different environments without needing detailed programming. This method is different from traditional self-driving technologies that often rely on expensive hardware and pre-mapped data. Instead, Wayve.ai employs end-to-end deep learning, making their solution more cost-effective for automakers. The company targets automakers and fleet operators, offering them adaptable and affordable solutions for driving automation. Wayve.ai has already partnered with major retailers in the UK to test its technology in delivery fleets, aiming to enhance mobility and sustainability in the automotive industry.

London, United KingdomHeadquarters

2017Year Founded

$1,272.3MTotal Funding

SERIES_CCompany Stage

Automotive & Transportation, AI & Machine LearningIndustries

201-500Employees

Benefits

Hybrid Work Options

Risks

Increased competition in San Francisco could dilute Wayve's market presence.

Regulatory challenges may delay the deployment of Wayve's technology with Uber.

Wayve's reliance on AI systems may face skepticism from traditional automakers.

Differentiation

Wayve uses embodied AI to adapt vehicles to any environment without explicit programming.

Its AV2.0 technology eliminates the need for costly robotic stacks and complex mapping.

Wayve's end-to-end deep learning approach offers a cost-effective solution for automakers.

Upsides

Wayve's partnership with Uber expands its market reach and data collection opportunities.

The expansion into the U.S. market taps into a larger talent pool and partnerships.

Generative AI models like GAIA-1 offer new ways to simulate driving scenarios.

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