Software Engineer, Machine Learning​/ ML Engineer, AI Engineer (Applied​/Software)

Aquent is partnering with an innovative technology company at the forefront of autonomous mobility, developing advanced software and artificial intelligence systems that are transforming the future of transportation. This organization is focused on building safe, reliable, and scalable autonomous technologies through cutting-edge machine learning, computer vision, and distributed software systems. Join a collaborative engineering environment where your technical expertise will directly contribute to advancing how autonomous systems perceive, understand, and navigate the world.

We are seeking an experienced Software Engineer, Fleet Mapping to contribute to the development of sophisticated mapping technologies that support next-generation autonomous vehicles. In this role, you will help design, develop, validate, and integrate machine learning models that identify important semantic features within complex environments. You will work on scalable, offline mapping pipelines that automate the detection and mapping of new features, helping improve the accuracy, efficiency, and reliability of autonomous navigation systems.

The ideal candidate brings strong C++ software engineering experience, a solid understanding of networking protocols, and experience building highly resilient distributed systems. Experience with robotics, computer vision, or mapping technologies is highly valued.

• Research, develop, implement, and train machine learning models to detect and classify semantic map elements used in autonomous navigation.
• Contribute to the development and enhancement of high-definition semantic mapping systems that support autonomous vehicle perception.
• Design, develop, and integrate software components into scalable, offline mapping pipelines.
• Drive automation of new mapping features to improve mapping efficiency, scalability, and accuracy.
• Curate, organize, validate, and label datasets used for machine learning model training and evaluation.
• Collaborate with engineering and validation teams to establish comprehensive model testing and validation pipelines.
• Leverage machine learning infrastructure and development tools to accelerate model training, experimentation, integration, and deployment.
• Develop and optimize C++ software components supporting high-performance mapping and distributed processing systems.
• Work with networking technologies and communication protocols to support reliable data exchange across distributed engineering systems.
• Identify and resolve performance, scalability, reliability, and integration challenges within complex software environments.
• Collaborate with software engineers, machine learning researchers, and cross-functional technical teams to deliver production-quality mapping capabilities.
• Contribute to engineering best practices, technical documentation, and continuous improvements to mapping systems and development workflows.

• 5+ years of professional software development experience using C++.
• Strong understanding of networking protocols and network communication principles, ideally including UDP.
• Experience designing, developing, or maintaining highly resilient distributed systems.
• Strong software engineering fundamentals, including debugging, performance optimization, testing, and system reliability.
• Ability to work effectively with complex software architectures and integrate new functionality into existing engineering systems.
• Excellent analytical and problem-solving skills, with the ability to troubleshoot technical challenges across interconnected systems.
• Strong communication and collaboration skills, including experience working with cross-functional engineering teams.
• Ability to work independently, navigate technical ambiguity, and contribute effectively in a fast-paced engineering environment.

• Experience with robotics, autonomous vehicles, or autonomous navigation technologies.
• Experience with 3D computer vision, image processing, or perception systems.
• Familiarity with high-definition maps, semantic mapping, or automated mapping pipelines.
• Hands-on experience developing, training, or validating machine learning models.
• Experience with semantic feature detection, object recognition, or environmental understanding.
• Experience working with large datasets, including data curation, labeling, and validation.
• Familiarity with machine learning infrastructure, model deployment, and production ML workflows.
• Experience with LiDAR, point clouds, or…