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资深技术主管经理,机器学习,视觉模型

机器翻译
查看雇主原标题Staff Tech Lead Manager, Machine Learning, Vision Models

Wayve · London

职位信息来自雇主公开的招聘页面。申请前请务必在雇主官网核实详情。

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发现指数 42/100,仅依据与该职位一起存储的证据计算。

42/100 发现指数
  • 新的雇主官方职位

分数构成

  • 时效性 (随职位发布时间变化)+18
  • 雇主官方来源+15
  • 稀有职位+1
  • 公司来源健康度+8

该职位未包含:已披露薪资、远程职位、提及签证担保、提及搬迁、未出现在监控的职位板上。

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职位描述

英文原文

该职位由雇主以英文发布,暂无中文版本,下面完整显示英文原文。 查看官方职位页面.

职位描述

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

As a Staff Tech Lead Manager on Wayve's Measurement team in AI Evaluation, based in our London office, you will lead a team building and productionising offline scene understanding models. You will directly manage four Senior Machine Learning Engineers and own the technical direction for turning technology from our on-vehicle models and Wayve Foundation Models into the robust, scalable scene understanding models that power our validation machine. You should be motivated by measurement and evaluation as a first-class engineering discipline.

Your team's mission is to predict and explain counterfactual outcomes, answering the question "what would have happened if we'd used a different driving model?", and to build the models that let Wayve understand coverage, mine rare events, and assess the behaviour of our end-to-end AV2.0 driver after on-road runs and in simulation. The offline environment gives the team headroom the vehicle never has: more compute per frame, larger models, and access to both past and future temporal context. The outputs are mission-critical, directly informing model development decisions and customer deliverables. This work currently spans several teams and sites, and you will pull it together into one coherent technical direction, working closely with on-vehicle modelling in AV Core, foundation model teams, Evaluation, simulation, and Model Development Platform across the UK and US.

Key responsibilities

• Lead and grow the team - directly manage four Senior MLEs in London; hire complementary talent across MLE, SWE, and data science profiles as scope grows; develop strong senior ICs and hold a high bar.

• Own the technical direction - guide the architecture for adapting shared on-vehicle models and Wayve Foundation Models for offline measurement use, exploiting the advantages of the offline environment: higher compute budgets, larger model capacity, and access to past and future temporal context.

• Own the roadmap - drive planning at

岗位职责

As a Staff Tech Lead Manager on Wayve's Measurement team in AI Evaluation, based in our London office, you will lead a team building and productionising offline scene understanding models. You will directly manage four Senior Machine Learning Engineers and own the technical direction for turning technology from our on-vehicle models and Wayve Foundation Models into the robust, scalable scene understanding models that power our validation machine. You should be motivated by measurement and evaluation as a first-class engineering discipline.

Your team's mission is to predict and explain counterfactual outcomes, answering the question "what would have happened if we'd used a different driving model?", and to build the models that let Wayve understand coverage, mine rare events, and assess the behaviour of our end-to-end AV2.0 driver after on-road runs and in simulation. The offline environment gives the team headroom the vehicle never has: more compute per frame, larger models, and access to both past and future temporal context. The outputs are mission-critical, directly informing model development decisions and customer deliverables. This work currently spans several teams and sites, and you will pull it together into one coherent technical direction, working closely with on-vehicle modelling in AV Core, foundation model teams, Evaluation, simulation, and Model Development Platform across the UK and US.

• Lead and grow the team - directly manage four Senior MLEs in London; hire complementary talent across MLE, SWE, and data science profiles as scope grows; develop strong senior ICs and hold a high bar.

• Own the technical direction - guide the architecture for adapting shared on-vehicle models and Wayve Foundation Models for offline measurement use, exploiting the advantages of the offline environment: higher compute budgets, larger model capacity, and access to past and future temporal context.

• Own the roadmap - drive planning at sprint, quarterly, and annual cadences; translate ambiguous business goals into concrete technical programmes; be equally comfortable setting multi-year direction and getting into the weeds of a sprint review.

• Drive production quality - build rigorous engineering practice for ML systems relied on for customer-facing deliverables; champion rig-agnostic, generalisable architectures with clean interfaces; hold the line on architectural quality in a fast-moving environment.

• Accelerate the development loop - ensure your team's models reduce the time between a driving-model iteration and reliable, actionable feedback; make the whole AV development loop faster.

• Partner and anticipate - align roadmaps with on-vehicle modelling and Evaluation teams across the UK and US; resolve technical conflicts at the right level; identify capability gaps 6-24 months out and build the case for investment to close them.

任职要求

In order to set you up for success as a Staff Tech Lead Manager at Wayve, we're looking for the following skills and experience.

• 8+ years in ML engineering, including hands-on computer vision with camera and/or lidar sensor data, and a track record of shipping production ML systems from research through to reliable, monitored, customer-facing software.

• 2+ years line-managing or tech-leading senior engineers, including hiring, developing, and retaining strong ICs, with the appetite to keep doing both halves of the TLM role.

• Staff-level technical depth that earns the trust of senior MLEs: transformer-based and multimodal architectures, foundation models, and large-scale training, with the ability to review designs and code credibly.

• Proficient in Python and ML frameworks (esp. PyTorch), with strong judgement about what production-grade looks like for ML systems.

• Strong cross-functional leadership: aligning roadmaps across teams and geographies, and communicating technical context and strategic direction clearly to engineers and senior leadership.

Desirable

• Knowledge of perception systems and 3D scene understanding for autonomy, such as cuboid detection, lane estimation, depth estimation, and large-scale semantic enrichment of driving scenes.

• Experience with offboard or offline models: auto-labelling, model distillation, temporal or world models, or other ways of exploiting compute that on-vehicle systems cannot.

• Familiarity with simulation or counterfactual evaluation methods for autonomous systems.

• Experience leading or partnering with distributed teams across UK and US time zones.

• MS or PhD in Computer Science, Engineering, or a related field.

This is a full-time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know.

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve

For US candidates only, please visit E-Verify Notice and Participation and Right to Work

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.

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