Woven Planet

Software Engineering Intern, Data Search

Woven Planet

internship

Posted on:

Location Type: Hybrid

Location: LondonUnited Kingdom

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Job Level

About the role

  • Accelerate autonomous driving by providing access to data collected by vehicles
  • Developing Machine Learning models for perception and prediction of human driving patterns
  • Identify real-world driving situations for validation and simulation
  • Engage with advanced data search problems to enhance system design expertise
  • Gain hands-on experience in practical engineering issues in an industry setting
  • Present project results to the team and stakeholders

Requirements

  • 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
  • Prior experience in the Autonomous driving domain (nice to have)
  • Hands-on experience with building a vector search system (nice to have)
  • Hands-on experience with Vision language models (nice to have)
Benefits
  • Promote both technical and professional development
  • Engage with advanced data search problems
  • Continuous feedback and well-defined goals
  • Support from mentors and managers

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
C++PythonMachine LearningEngineering first principlesVector search systemVision language models
Soft skills
Problem-solvingCommunication
Certifications
Master's Degree in Computer ScienceMaster's Degree in Computer EngineeringMaster's Degree in Computer Systems