Machine Learning Engineer

4 days ago

Vancouver, British Columbia, Canada Wayve Full time

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.

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.

At Wayve, 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 are looking for a Machine Learning Engineer to drive the development and productionization of end-to-end neural networks for autonomous driving. In this role, you will collaborate closely with Production and Research teams to develop, test, scale, and deploy cutting-edge ML models.

The ideal candidate will have deep technical experience in large scale deep learning, multimodal data pipelines and curation, and a passion for efficiency, engineering excellence and evaluation. If you're excited to innovate in Foundation Models and the autonomous driving space, please get in touch

About you

Essential:

3+ years experience shipping AI and ML features in production environments Strong programming skills in Python, including experience with deep learning frameworks such as PyTorch, Numpy, Pandas etc. Solid understanding of training, validation, and testing methodologies for deep learning models Experience in designing efficient large-scale machine learning systems, including data/model parallelism techniques, model optimization and quantization Commitment to excellence in data engineering, with an appreciation for quality, curation, large scale datasets and scaling laws Passion to take research ideas to production

Desirable:

MS or PhD in Computer Science or Engineering with specialism in Machine Learning, Robotics, Artificial Intelligence, Natural Language Processing, Computer Vision  Record of publication at places like CoLM, CoRL, CVPR, ICCV, AAAI, ICML, NeurIPS, RSS, ICRA, ACL, EMNLP 

This is a full-time role based in our office in Vancouver. 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.

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.

For more information visit Careers at Wayve. 

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

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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