Woven by Toyota Logo

Woven by Toyota

Software Engineering Intern, Data Search

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Hybrid
London, England
Hybrid
London, England

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Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.


Our work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud & AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.


 

TEAM

Our Data Platform team is working on accelerating autonomous driving by providing access to petabytes of  data collected by our fleet of autonomous and non-autonomous vehicles. Efficient, fast and cost-effective access to data at large scale is key to tackle the hardest problems in AD/ADAS, from developing the Machine Learning (ML) models for perception and prediction of human driving patterns, to increasing the sophistication of our validation and simulation by identifying rare and interesting real-world driving situations. The data ecosystem developed by the London team is a key building block for developing and testing modern AD/ADAS products that will impact millions of customers.

 

Our ML and Data pipelines are built on-top of the open-source Flyte orchestration framework and are deployed to AWS. Pipeline code is written in Python. We use SQS and Kafka to automate data connections and leverage BigQuery and Elasticsearch for data storage. We believe strongly in automation and testing to ensure delivery of robust and correct systems. We are a distributed team, working in the UK and US.

 

WHAT WE WILL GIVE YOU?

The internship period has two primary academic objectives. First, the intern intends to advance their system architecture design skills to tackle cutting-edge mobility challenges in scalable data search. Second, the intern seeks to acquire hands-on experience in addressing practical engineering issues in an industry setting. Throughout this internship, the intern will deepen their understanding of system design and software engineering while exploring innovative solutions for multimodal search.

 

At Woven by Toyota, our internships are crafted to promote both technical and professional development. You will have the chance to engage with advanced data search problems, enhancing your system design expertise and gaining experience in bringing solutions to production. With continuous feedback and well-defined goals, you will receive support from mentors and managers throughout the experience. At the conclusion of the internship, you will present your project results to the team and other interested stakeholders.

MINIMUM QUALIFICATIONS

  • Currently pursuing a master's degree in Computer Science, Computer Engineering, Computer Systems, or similar.
  • Proficiency in developing with one or more of the following programming languages : C++, Python
  • Applied knowledge and understanding of engineering first principles
  • Proven ability to tackle complex engineering problems.
  • Basic working knowledge of cloud applications (e.g., AWS, GCP, Azure)
  • Basic knowledge of Serverless Data Warehouse e.g., BigQuery/Snowflake
  • Understanding of Machine Learning fundamentals
  • Strong written and verbal communication skills

NICE TO HAVES

  • Prior experience in Autonomous driving domain
  • Hands-on experience with building vector search system
  • Hands-on experience with Vision language models

Our Commitment

・We are an equal opportunity employer and value diversity.

・Any information we receive from you will be used only in the hiring and onboarding process. Please see our privacy notice for more details.

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