Senior Machine Learning Engineer, AI Performance

Wayve·Londonsenior

En corto

→Ingeniero ML senior que entrega modelos listos para producción en vehículos autónomos.
→Trabaja en optimizar modelos de PyTorch para cumplir restricciones de rendimiento en tiempo real.
→Destacado: trabajo en sistemas mapless y hardware-agnostic, con foco en delivery real con impacto en la carretera.

Comfort operating at multiple levels of abstraction — from high-level model behaviour down

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

🎧¿Llegás a la entrevista? Llevá el copiloto. Nuestra extensión escucha la entrevista en vivo y te muestra anclas de 3-4 palabras desde tu CV y tu preparación — mirás, conectás, hablás. Gratis. Ver la extensión →

¿Qué piden?

✓Experiencia demostrable mejorando el rendimiento en sistemas de producción bajo restricciones (latencia, memoria, potencia, etc.).
✓Experiencia práctica entrenando e iterando modelos profundos en PyTorch, no solo usando herramientas de alto nivel.
✓Dominio de al menos una pila/entorno (TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL) y capacidad para aprender rápidamente otras.
✓Capacidad para operar a múltiples niveles de abstracción: desde comportamiento del modelo hasta ejecución de kernels.
✓Familiaridad con técnicas de optimización de modelos como cuantización y distillación (con experiencia práctica preferible).
✓Habilidad para razonar entre niveles de abstracción y comunicar trade-offs con equipos y stakeholders.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PyTorchTensorRTCUDAQualcomm QNNTritonOpenCLlow-rank methodsquantisationdistillationablation studies

¿A quién escribirle en Wayve?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

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 We’re looking for a Senior Machine Learning Engineer to join a high-ownership team responsible for delivering production-ready model releases as our OEM engagements and release cadence accelerate. This is an applied, delivery-focused MLE role—ideal for engineers who love shipping real systems and iterating quickly. You’ll work on taking models from “works in training” to “meets product constraints,” partnering closely with teams downstream (e.g., inference/performance specialists) to ensure models are ready for deployment on-vehicle. As model capability grows, you’ll help keep the system within tight runtime constraints using a practical model optimisation techniques (e.g., quantisation, distillation, low-rank methods) where appropriate. Key responsibilities • Own end-to-end delivery of model releases, from initial requirements through training, evaluation, iteration, and final readiness for deployment. • Train and iterate on PyTorch models with a strong experimental approach (hypothesis-driven iteration, ablations, clear evaluation criteria). • Debug and improve model performance using strong analytical skills—identifying regressions, root-causing issues, and proposing fixes. • Apply optimisation techniques (e.g., quantisation and distillation where beneficial), understanding trade-offs and when methods are appropriate. • Collaborate cross-functionally with adjacent ML and performance engineering teams to hand off models, define bottlenecks, and align on optimisation priorities. • Communicate clearly with stakeholders to align on delivery timelines, trade-offs, and readiness criteria. About you In order to set you up for success in this role at Wayve, we’re looking for the following skills and experience: Essential • Proven experience improving performance in production systems with tight constraints (latency, memory, bandwidth, power/thermal, or cost). • Strong hands-on experience training and iterating on deep learning models in PyTorch (not just using high-level tooling). • Strong proficiency with at least one relevant stack/toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL) and confidence learning adjacent frameworks quickly. • Comfort operating at multiple levels of abstraction — from high-level model behaviour down to low-level kernel/runtime execution. • Familiarity with model optimisation concepts such as quantisation and/or distillation (hands-on is a strong signal, but not a strict requirement if the fundamentals are solid). • Ability to reason across multiple levels of abstraction—from high-level model behaviour down to practical runtime/latency implic

¿Buscando algo parecido?

Dejá tu email y te avisamos cuando salgan vacantes que coincidan con tu perfil.

No apliques sin prepararte

Investigamos quién te entrevista, adaptamos tu CV y te ensayamos en vivo — gratis la primera.