Avride
Overview
Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With over seven years of experience, 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 looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In this role, you will conduct experiments, manage large-scale datasets, and implement deep learning models tailored for autonomous systems. You will utilize cloud platforms, orchestration tools, and machine learning frameworks to develop scalable and efficient solutions. Additionally, you will analyze the latest research, assess the applicability of emerging deep learning techniques, and drive innovation in autonomous vehicle technology. What You'll Do
Develop and Optimize Machine Learning Models:
Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness. This may include developing models for understanding a self-driving vehicle’s surroundings or predicting the intentions of other road users. Curate and Manage Large-Scale Datasets:
Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation. Enhance and Maintain Training Pipelines:
Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring. Improve Model Deployment and Efficiency:
Optimize inference performance, model compression, and deployment across various hardware platforms. Explore and Apply Cutting-Edge ML Techniques:
Stay up to date with advancements in deep learning and experiment with novel approaches to improve model performance. Collaborate with Cross-Functional Teams:
Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems. What You'll Need
Strong understanding of fundamental machine learning algorithms and neural network techniques. Expertise in at least one modern machine learning domain, such as computer vision, large language models, or generative AI. At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment. 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 by reviewing research papers, technical reports, and documentation. Strong collaboration and communication skills, with the ability to align technical work with business objectives and drive results. Nice to 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. Proven ability to set and achieve mid- and long-term goals, prioritize tasks, and meet deadlines independently. Experience working in cross-functional teams within a multidisciplinary environment. Publications in top-tier ML conferences or contributions to patent applications or ML-related open-source projects. Apply for this job
Candidates are required to be authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available. Voluntary Self-Identification For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file. As set forth in Avride’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows: A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability. A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service. An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense. An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985. Voluntary Self-Identification of Disability Form CC-305 OMB Control Number 1250-0005; Expires 04/30/2026 PUBLIC BURDEN STATEMENT: According to the Paperwork Reduction Act of 1995, no persons are required to respond to a collection of information unless such collection displays a valid OMB control number. This survey should take about 5 minutes to complete.
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Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With over seven years of experience, 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 looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In this role, you will conduct experiments, manage large-scale datasets, and implement deep learning models tailored for autonomous systems. You will utilize cloud platforms, orchestration tools, and machine learning frameworks to develop scalable and efficient solutions. Additionally, you will analyze the latest research, assess the applicability of emerging deep learning techniques, and drive innovation in autonomous vehicle technology. What You'll Do
Develop and Optimize Machine Learning Models:
Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness. This may include developing models for understanding a self-driving vehicle’s surroundings or predicting the intentions of other road users. Curate and Manage Large-Scale Datasets:
Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation. Enhance and Maintain Training Pipelines:
Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring. Improve Model Deployment and Efficiency:
Optimize inference performance, model compression, and deployment across various hardware platforms. Explore and Apply Cutting-Edge ML Techniques:
Stay up to date with advancements in deep learning and experiment with novel approaches to improve model performance. Collaborate with Cross-Functional Teams:
Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems. What You'll Need
Strong understanding of fundamental machine learning algorithms and neural network techniques. Expertise in at least one modern machine learning domain, such as computer vision, large language models, or generative AI. At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment. 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 by reviewing research papers, technical reports, and documentation. Strong collaboration and communication skills, with the ability to align technical work with business objectives and drive results. Nice to 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. Proven ability to set and achieve mid- and long-term goals, prioritize tasks, and meet deadlines independently. Experience working in cross-functional teams within a multidisciplinary environment. Publications in top-tier ML conferences or contributions to patent applications or ML-related open-source projects. Apply for this job
Candidates are required to be authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available. Voluntary Self-Identification For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file. As set forth in Avride’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows: A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability. A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service. An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense. An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985. Voluntary Self-Identification of Disability Form CC-305 OMB Control Number 1250-0005; Expires 04/30/2026 PUBLIC BURDEN STATEMENT: According to the Paperwork Reduction Act of 1995, no persons are required to respond to a collection of information unless such collection displays a valid OMB control number. This survey should take about 5 minutes to complete.
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