About the team

Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With the recent launch of our robotaxi service in Dallas, we are accelerating innovation and redefining the future of mobility. Our team builds self-driving solutions from the ground up, with machine learning at the core of our development pipeline to enable safe and intelligent navigation. We design and deploy state-of-the-art models to address key challenges in autonomous systems, utilizing advanced deep learning architectures such as Convolutional Neural Networks (CNNs), Transformers, and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard applications, ensuring robust and efficient operation. Your work will directly contribute to enhancing the performance, safety, and reliability of Avride's autonomous vehicles and delivery robots.

About the role

We are hiring experienced Machine Learning Engineers across Senior, Staff, and Principal levels. to site onsite in Austin, Texas. Whether you're a strong individual contributor ready to take on complex technical challenges, or a seasoned technical leader looking to take on complex technical challenges we want to hear from you.

In this role, you will drive the development and deployment of machine learning solutions for some of the hardest problems in autonomy conducting experiments, managing large-scale datasets, and implementing deep learning models tailored for real-world autonomous systems. At more senior levels, you will also define technical strategy, mentor engineers, and influence how ML is practiced across the organization.

What you'll do

• Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness — including models for environmental perception and predicting the behavior of other road users. At Staff and Principal levels, you will set the technical vision for entire model families and drive architectural decisions across teams.
• Curate and Manage Large-Scale Datasets: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation. Senior+ engineers will establish standards and tooling that scale across the organization.
• Enhance and Maintain Training Pipelines: Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring. Staff and Principal engineers will own the long-term roadmap for training infrastructure.
• Improve Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across various hardware platforms.
• Explore and Apply Cutting-Edge ML Techniques: Stay current with advancements in deep learning and lead the evaluation and adoption of novel approaches. Principal engineers are expected to identify opportunities before they become industry standard.
• Collaborate and Lead Across Teams: Work closely with researchers, software engineers, and robotics experts to integrate ML into real-world autonomous systems. At Staff and Principal levels, you will drive alignment across functions, mentor junior and senior engineers, and serve as a technical authority across the org.

What you'll need

• Strong understanding of fundamental machine learning algorithms and neural network techniques.
• Deep expertise in at least one modern ML domain, such as computer vision, large language models, or generative AI.
• Senior: 4+ years of experience developing neural network-based algorithms, including data collection, training, and deployment.
• Staff: 7+ years of experience, with a track record of leading significant technical initiatives and influencing engineering practices beyond your immediate team.
• Principal: 10+ years of experience, with demonstrated impact at an organizational or industry level — setting multi-year technical direction and driving outcomes across multiple teams.
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, along with PySpark, NumPy, and SciPy.
• Working knowledge of C++ and SQL.
• Ability to quickly absorb new concepts from research papers, technical reports, and documentation.
• Strong collaboration and communication skills, with the ability to align technical work with business objectives at all levels of the organization.

What you must have

• Advanced degree in Computer Science, Machine Learning, Robotics, or a related field.
• Experience developing ML algorithms for autonomous vehicles or robotics applications.
• Familiarity with neural network deployment and optimization tools such as Triton, TensorRT, or similar frameworks.
• Publications in top-tier ML conferences, contributions to patent applications, or ML-related open-source projects.
• For Staff/Principal: experience building and scaling ML teams, defining org-wide technical standards, or driving cross-company research agendas