Offer summary

Qualifications:

Masters or PhD in a relevant field, graduating within 12 months of internship completion., Strong programming skills in Modern C++ and/or Python., Familiarity with deep learning frameworks such as Pytorch., Excellent communication, interpersonal, and problem-solving skills..

Key responsabilities:

Implement state-of-the-art onboard multimodal multitask ML perception models and finetune them for performance improvement.

Develop custom adaptations to enhance model performance on specific datasets.

Conduct research in multiview sensor fusion and scene understanding with a focus on anomaly detection.

Design and perform experiments, sharing findings potentially as peer-reviewed publications.

Job description

Who we are:

Glydways is reimagining what public transit can be. We believe that mobility is the gateway to opportunity—connecting people to housing, education, employment, commerce, and care. By making transportation more accessible, affordable, and sustainable, we empower communities to thrive and unlock economic and social prosperity.

Our mission is to revolutionize transit with a solution that delivers high capacity, exceptional user experiences, unmatched affordability, and minimal environmental impact.

The Glydways system is a groundbreaking network of carbon-neutral, interconnected transit pathways powered by standardized autonomous vehicles on dedicated roadways. Operating 24/7 with on-demand access, it offers personalized and efficient mobility—without the burden of heavy upfront infrastructure costs or ongoing taxpayer subsidies.

With Glydways, we’re building more than a transportation system; we’re creating a future where everyone, everywhere, has the freedom to move.

Meet the team:

We are looking for a highly motivated research intern with a strong background in machine learning to join our ML Perception team and apply your expertise to real-world multi agent autonomous driving and infrastructure challenges to help Glydcars see. In this role, you will focus on multimodal efficient deep learning for safety critical systems with built in redundancy and robustness. Collaborating with a multidisciplinary team, you will develop innovative models and algorithms to enhance our perception stack.

Roles & Responsibilities:

Implement state-of-the-art onboard multimodal multitask ML perception models, and finetune them to improve performance
Develop custom adaptations (such as layers, loss functions, etc.) to improve performance on our datasetResearch and development in various areas, including multiview sensor fusion for redundancy, robustness, and safety critical operation; and scene understanding with a focus on anomaly detection.
Design and perform experiments, and share and present findings, potentially as a peer-reviewed publication.
Work with multimodal (camera, lidar, radar) datasets from a multiagent autonomous system

Knowledge, Skills and Abilities:

Masters / PhD graduating within 12 months of internship completion
Strong programming skills (Modern C++ and/or Python)
Familiarity with deep learning frameworks such as Pytorch
Excellent communication and interpersonal skills;
Strong problem-solving and research skills
Candidates with experience in early fusion models and/or semantic segmentation models are preferred

Glydways provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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