Autonomous Driving - Internship in Machine Learning

Job Description:

Job Description

We are looking for an accomplished student in the ML space with strong technical skills to work with us on the design, implementation, training and roll-out the next generation of AI-enabled triage and Forensics on large scale data from our robot fleets, a core component of the realization of self-driving vehicles. As an intern on the team, you will be working on all important aspects of the implementation, in order to enable our R&D teams.
Responsibilities include:
* Design, implement and roll-out important aspects of our state-of-the-art forensics tooling for robotics applications: data processing, model development, validation
* Work on data pipelines, model training and validation, and performance evaluation
* Support the integration and testing of our framework, as well as its continuous operation
* Continuously drive innovation by bringing the latest developments in academia to the table and evaluate them as potential candidate for implementation

Candidate Requirements:

Qualifications

Required:
* Currently enrolled in a Masters or PhD program
* Minimum GPA of 3.0
* Hands-on experience with Pytorch for model development, training and testing in a Linux environment
* Solid understanding of machine learning fundamentals and hands-on experience with training and fine-tuning models.
* Strong understanding of the machine learning lifecycle-from data preprocessing and model training to evaluation, deployment, and monitoring
* Experience with state-of-the-art model architectures, including transformers, CNNs, LSTMs, …
* Familiarity with raw data as well as meta-data management system (e.g. Databricks)
* Experience with machine learning platforms like Azure ML
* Usage of modern API frameworks
* Strong communication and team collaboration skills
Bonus points:
* Understanding of the technologies behind self-driving vehicles and/or general robotics
* Familiarity with agile working methodologies and tools (e.g. ADO)
* Ownership- and quality-driven