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Wayve interview, decoded.

Updated · Sources at the end

Wayve prints its interview loop in each job ad, with the team's own timings, and most engineering ads now name a hiring manager interview. The usual shape: a 30-minute recruiter screen, a hiring manager interview, programming, two to three hours of system design and domain deep dives, and a final 45 minutes to an hour on the mission and values. Staff roles add a technical leadership interview. For machine learning engineers the round people talk about is PyTorch debugging, which several ML teams now name in their ads: candidates on Glassdoor describe an hour with a Google Colab notebook that trains a convolutional network, where the job is to find and fix what is broken. Software engineers report a live coding round with a technical lead and a broader architecture discussion.

Wayve trains cars to drive from data rather than hand-written rules. It raised a $1.2B Series D at an $8.6B valuation in February 2026, led by Eclipse, Balderton and SoftBank with Microsoft, NVIDIA, Uber and three carmakers taking part, and its robotaxis went live on Uber in London in September 2026 with a safety driver on board.

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01

Who Wayve hires

Wayve hires machine learning engineers and research scientists (perception, vision models, reinforcement learning, foundation models for driving and robotics), software engineers for the data platform, fleet management, evaluation tools and the software that runs on the car, embedded and systems engineers, and site reliability engineers. On 9 November 2026 it had 173 open roles, about 117 in engineering and science; by location most were in Sunnyvale (72) and London (51), then Tokyo, Leonberg, Detroit and Herzliya. The ads describe a hybrid model across hubs in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg, with time in workshops and labs alongside the vehicles.

Wondering whether your resume reads like someone Wayve hires? Get a free resume review.

Every ad gives the same four parts, but each team sets what goes in them and for how long. What the technical hours contain depends on which side of the company you join.

  • Track · ML

    Machine learning engineering

    Programming, with PyTorch debugging named in the ads for the Gaia, reinforcement learning and application software teams; a hiring manager interview; then systems and domain interviews of up to three hours. The senior ADAS ad puts programming and system design first (two hours), then an hour with the hiring manager on the domain. Glassdoor adds a deep learning case study. The domain deep dive follows your team: perception, 3D and tracking for ADAS, vision models, reinforcement learning.

  • Track · SWE

    Software engineering

    The Map & Route ad sets it out: 60 minutes of Python programming and 45 with the hiring manager, then 60 minutes of systems design and 60 of domain, then 45 on mission and values. Candidates describe the coding hour with a technical lead and an architecture discussion on scale and open-ended product problems. Data roles work at petabyte scale, with data growing from hundreds of petabytes towards exabytes, so expect the design questions to live there.

02

What is the Wayve interview process?

The stages are Wayve's own: on 9 November 2026, 106 of its 117 engineering and science ads set out the process, 67 of them with a hiring manager interview, and timings vary by team. The rounds below give the usual shape from the ads cited at the foot; what happens inside them comes from Glassdoor reviews and candidate accounts. Glassdoor puts the average at about 24 days; one account puts it at two weeks.

01
Recruiter screen
25 to 30 minutes

Your background, current situation and interests, and Wayve's company and hiring context, as the ads put it. Have a clear answer to why Wayve's approach to driving interests you.

02
Hiring manager interview
45 minutes to an hour

Now in most engineering ads, either as its own call (an hour, in the Staff ML Engineer, Data Curation ad) or inside the competency interviews (45 minutes, in the Software Engineer, Map & Route ad). The platform engineering ads list role fit, technical breadth, problem-solving, ownership and collaboration.

03
Competency interviews: programming
About an hour of programming, often with the hiring manager in the same block

A live coding round, usually Python; some ads add code review. Software engineers report the coding led by a technical lead and judged on code quality and reasoning. Some ML ads, such as senior ADAS, put programming and system design together here for two hours.

04
PyTorch debugging
Part of the programming block, in a Google Colab notebook

Named in Wayve's own ads for the Gaia, reinforcement learning and application software ML teams. Candidates describe a notebook that trains a CNN and does not work: find the errors, fix them, and explain what each one did to training. The section below goes through what to check.

Machine learning roles
05
Deep-dive technical interviews
One to three hours

System design and a domain interview on your specialism against the team's problems; staff and senior roles often add a technical leadership interview. ML candidates report a deep learning case study; one reported question asks how you would find every example in a dataset of telemetry and video where the car had to brake hard because another vehicle cut in.

06
Mission and values
30 minutes to an hour

Why embodied AI, how you work, and whether you want to help build a company whose playbook, in its own ads, is still being written. Some ads, such as reinforcement learning, name a director or VP for this round.

03

Wayve PyTorch debugging interview: what to check in the notebook

A checklist for the round

Wayve's ads for several machine learning teams name PyTorch debugging among the interviews. Machine learning candidates describe one hour with a Google Colab notebook that trains a convolutional network and has errors to find and fix. Nobody has published the bugs themselves, and they will change. These are the faults a broken training loop usually contains, in the order worth checking, so you have a routine instead of a guess.

  • Does it run at all?: Read the first stack trace carefully. Shape mismatches between the last convolution and the first linear layer, and tensors on different devices (one on the GPU, one on the CPU), are the usual crashes.
  • Is the data right?: Show a few images with their labels before touching the model. Look for labels that do not match, a missing or doubled normalisation, channels in the wrong order, and a train set that is not shuffled.
  • Is the loss right for the output?: Cross-entropy in PyTorch expects raw scores and class indices; a softmax before it, or one-hot targets, quietly breaks training. Check the loss is averaged the way you think.
  • Is the training step in the right order?: zero_grad, forward, loss, backward, step. A missing zero_grad lets gradients pile up; a step before backward does nothing useful.
  • Are train and eval modes switched?: model.train() for training and model.eval() with torch.no_grad() for evaluation, or dropout and batch norm behave wrongly and the validation numbers lie.
  • Can it overfit one batch?: Train on a single small batch. If the loss will not go near zero, the bug is in the model or the loop, not the data size. Then check the learning rate and the optimizer's parameter list.

Say what each bug did to training as you fix it. The round is as much about how you reason through a broken run as about the fixes.

The rest of the loop depends on your role. Pick it, or paste the posting, and Calibrd predicts the rounds and questions you are likely to get at Wayve.

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04

What Wayve screens for

Wayve's ads close with a warning that it is not a settled company, and the final interview checks you are fine with that.

  • Ownership where the playbook is still being written
  • Pragmatic, measurable progress on real driving performance
  • End-to-end work across data, training, evaluation and iteration
  • Care for safety on real roads
  • Mission alignment with embodied AI
05

Wayve interview questions

Candidate-reported themes

Candidates describe the formats in more detail than the questions. The reported ones are below; the technical themes come from the reports and the ads.

Behavioural & motivation

  • Why Wayve, and why embodied AI?
  • Tell me about a model or system you took from data to production.
  • How do you decide what to fix next when a model underperforms?
  • Tell me about working somewhere without a settled process.

How to structure your answer out loud →

Technical

  • A Colab notebook trains a convolutional network and it does not work. Walk me through how you find the errors, fix them, and explain what each one did to training.PyTorch debugging: A broken CNN training notebook in Colab: find the faults, fix them, explain themListening for: Checking routine · Knows common bugs · Explains effects
  • How would you find every example in a dataset of telemetry and video where the car had to brake hard because another vehicle cut in?Data mining for driving: Reported: find every emergency brake caused by a cut-in across telemetry and videoListening for: Right signals · Works at scale · Checks results
  • Practice: Design an auto-labelling pipeline that produces 3D boxes and tracks for driving data. How do you check the labels are good enough?Perception: Detection, segmentation, 3D and tracking, and auto-labelling pipelines for ADASListening for: Pipeline design · Label quality · Tied to driving
  • Design a pipeline that ingests hundreds of petabytes of driving data, where one bad segment must not block the rest.Data platform design: Ingesting hundreds of petabytes of driving data, where one bad segment must not block the pipelineListening for: Failure isolation · Scale and storage · Searchable data
  • Practice: Given a stream of sensor readings, return the maximum of every window of k consecutive readings. Talk through the approach and the complexity.Data structures and algorithms: A live coding hour in the competency interviewsListening for: Correct approach · Complexity · Code quality

These are the reported themes, and your loop is role-specific. Paste the actual posting and Calibrd predicts the questions for that exact role and level. How the questions are predicted →

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06

Pay

Software engineer, data ingestion, Sunnyvale (posted)$209,700–$266,800 base plus equity
Software engineer, simulation, Sunnyvale (posted)$209,000–$310,000 base plus equity
Senior software engineer, OS, robot software, Sunnyvale (posted)$200,000–$250,000 base plus equity
Senior software engineer, fleet management, Sunnyvale (posted)$209,700–$238,250 base plus equity
Senior ML engineer, vision models, Sunnyvale (posted)$311,850–$389,400 base
Staff ML engineer, data curation, Sunnyvale (posted)$390,000–$460,000 base
Software Engineer, Greater London (Levels.fyi, self-reported)£129K median total pay

Wayve posts base pay ranges on its Sunnyvale ads (read 9 November 2026), not on its London engineering ads: $176,500 to $198,650 for a fleet management software engineer, $209,700 to $238,250 for a senior one, $200,000 to $250,000 for a senior software engineer on robot operating systems, $209,000 to $310,000 for a simulation software engineer, $209,700 to $266,800 for a data ingestion engineer, $311,850 to $389,400 for a senior machine learning engineer on vision models, and $390,000 to $460,000 for a staff machine learning engineer on data curation, most with equity. For London, the only figure is self-reported: Levels.fyi puts the median software engineer package at Wayve in Greater London at £129K from 50 submissions (page updated and read 9 November 2026). The ads also promise salaries benchmarked yearly, relocation and visa sponsorship where it applies. Calibrd benchmarks the pay on any posting you scan against its level and location.

Applying to Wayve? Paste the posting and see whether they’d shortlist you →

07

How to prepare for a Wayve interview

  1. Break a PyTorch training loop on purpose, then fix it against a clock. Run through data, loss, step order, modes and overfitting one batch until it is a habit.
  2. Revise data structures and algorithms for a live hour, usually in Python. Most engineering ads list a programming interview.
  3. Prepare a design for driving data at scale: ingesting petabytes, letting one corrupt segment fail without blocking the rest, and making it searchable for rare events.
  4. Practise mining a dataset for rare events, like the reported emergency brake question: what signals you would use, how you would check the results.
  5. Read about end-to-end driving before the values round and have a view on it. The final hour is about the mission.

This guide covers Wayve's machine learning and software engineering loops. Hardware, fleet operations and field roles run a different process. For management and leadership roles the loop is similar but the bar shifts to people, delivery and strategy, so pair it with the leadership interview prep hub. The bar for your exact role comes from the role-by-role guides, and the prep that actually transfers is spoken, so run a mock interview before the real one.

Also interviewing at Helsing, Saronic or ASML? Their guides follow the same format, from the first screen to the offer.

Knowing the questions isn’t the same as answering them out loud. Run a Wayve mock: spoken answers, coached on the spot. Your first mock is free.

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08

FAQ & sources

What is Wayve's interview process?

The stages are Wayve's own: on 9 November 2026, 106 of its 117 engineering and science ads set out the process, 67 of them with a hiring manager interview, and timings vary by team. The stages, in order: Recruiter screen; Hiring manager interview; Competency interviews: programming; PyTorch debugging; Deep-dive technical interviews; Mission and values.

What does Wayve look for in candidates?

Wayve's ads close with a warning that it is not a settled company, and the final interview checks you are fine with that. Ownership where the playbook is still being written; Pragmatic, measurable progress on real driving performance; End-to-end work across data, training, evaluation and iteration; Care for safety on real roads.

What questions does Wayve ask in interviews?

Candidates describe the formats in more detail than the questions. Technical themes: PyTorch debugging; Data mining for driving; Perception; Data platform design; Data structures and algorithms.

What is the Wayve PyTorch debugging interview?

Wayve's ads for several machine learning teams name PyTorch debugging among the interviews. Machine learning candidates describe one hour with a Google Colab notebook that trains a convolutional network and has errors to find and fix. Covered on this page: Does it run at all; Is the data right; Is the loss right for the output; Is the training step in the right order; Are train and eval modes switched; Can it overfit one batch.

How much does Wayve pay?

Software engineer, data ingestion, Sunnyvale (posted): $209,700–$266,800 base plus equity; Software engineer, simulation, Sunnyvale (posted): $209,000–$310,000 base plus equity; Senior software engineer, OS, robot software, Sunnyvale (posted): $200,000–$250,000 base plus equity; Senior software engineer, fleet management, Sunnyvale (posted): $209,700–$238,250 base plus equity. Wayve posts base pay ranges on its Sunnyvale ads (read 9 November 2026), not on its London engineering ads: $176,500 to $198,650 for a fleet management software engineer, $209,700 to $238,250 for a senior one, $200,000 to $250,000 for a senior software engineer on robot operating systems, $209,000 to $310,000 for a simulation software engineer, $209,700 to $266,800 for a data ingestion engineer, $311,850 to $389,400 for a senior machine learning engineer on vision models, and $390,000 to $460,000 for a staff machine learning engineer on data curation, most with equity.

How do I get a job at Wayve?

Wayve hires machine learning engineers and research scientists (perception, vision models, reinforcement learning, foundation models for driving and robotics), software engineers for the data platform, fleet management, evaluation tools and the software that runs on the car, embedded and systems engineers, and site reliability engineers. On 9 November 2026 it had 173 open roles, about 117 in engineering and science; by location most were in Sunnyvale (72) and London (51), then Tokyo, Leonberg, Detroit and Herzliya. Hiring runs in 6 stages, starting with Recruiter screen.

How do I prepare for a Wayve interview?

Break a PyTorch training loop on purpose, then fix it against a clock. Run through data, loss, step order, modes and overfitting one batch until it is a habit. Revise data structures and algorithms for a live hour, usually in Python. Most engineering ads list a programming interview.

Interview processes change. This reflects widely-reported and sourced conditions as of 2026 — confirm specifics with your recruiter, and treat it as a map rather than a guarantee.

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Wayve Interview: PyTorch Debugging Round, ML Loop — Calibrd