About team

Avride is at the forefront of autonomous mobility, developing and deploying state-of-the-art self-driving cars and delivery robots. We’re shaping the future of transportation and logistics—and our Labeling Team plays a vital role in bringing that vision to life.

The Labeling Backend Team builds the data infrastructure that powers groundbreaking research and development across our labeling pipelines, data preparation workflows, and model training processes. The high-quality labeled data we deliver is critical to advancing our core technologies and supports the diverse range of models that drive our entire business.

About the Role

We are looking for a Research Engineer to improve the quality and representativeness of datasets powering our self-driving systems. You will design algorithms and tools for auto-labeling, data mining and dataset monitoring, combining strong Python engineering with applied ML concepts. Your work will directly enhance data efficiency, reduce labeling costs, and improve model performance.

What You'll Do

• Design and implement algorithms that optimize annotation, including auto-labeling systems that reduce manual effort and increase throughput
• Build data-mining and active-learning pipelines to surface the highest-value samples for training
• Create dataset-quality monitoring systems identifying noise, redundancy, and low-value data
• Develop analytics platforms (databases, dashboards, reporting) to track dataset quality and coverage over time
• Collaborate with ML and Perception teams to integrate research results into production workflows
• Explore emerging approaches (vision-language models, weak supervision, uncertainty estimation) to expand dataset quality and automation

What You’ll Need

• Bachelor’s or Master’s degree in Computer Science or related field
• Strong Python skills for algorithm development and prototyping
• Solid understanding of ML concepts (metrics, evaluation, dataset sampling, etc.)
• Experience with data processing and analysis at scale
• Ability to move between research prototyping and production engineering
• Strong analytical mindset and curiosity to dig deep into data quality problems

Nice to Have

• Experience with auto-labeling, weak supervision, or human-in-the-loop ML
• Exposure to 3D data (point clouds, sensor fusion, 3D annotation pipelines)
• Background in AV, robotics, or large-scale ML dataset development
• Experience with foundation models / VLMs
• Workflow orchestration systems (Argo, Airflow, etc.)
• Backend engineering experience (APIs, ORMs, databases)
• Experience building dashboards or analytics systems (Grafana, Superset, etc.)

About the Team

Avride is a rapidly developing company in the autonomous vehicle and delivery robot industry. We develop autonomous vehicle technology from scratch, leveraging the strong technical background of our core team and over seven years of experience in autonomous vehicle development. The Localization team is responsible for providing precise rover location to all the components of the autonomous rover pipeline, like perception, behavior layer, and control. We calculate the position and the orientation of the rover with centimeter and fraction-of-a-degree accuracy, dozens of times per second, and in all conditions. Our most valuable asset is people, each with many years of experience in robotics, EKF, ICP, SLAM algorithms, distributed data processing, software architecture, and machine learning, working together as a motivated, effective, and friendly team.

About the Role

What You'll Do

• Develop the cloud mapping subsystem with graph optimization at its core.
• Develop the Sensor Fusion Localization subsystem, which combines the measurements of multiple sensors (LiDAR, IMU, GNSS, etc.) to calculate rover position to centimeter precision and orientation to 0.1-degree precision.
• Support sister development and operation teams on issues related to localization.

What You'll Need

• 3+ years of professional software engineering experience
• Strong C++ programming skills
• Solid understanding of algorithms, data structures, and software design patterns
• Solid soft skills — intra- and inter-team collaboration, business-driven development focus, planning and getting-things-done, effective and respectful communication

Nice to Have

About the Team

Avride is a fast-growing leader in the autonomous vehicle and delivery robot industry. We are building the future of mobility from the ground up, backed by a core team with over seven years of pioneering experience in autonomous technology.

Our Control team is the driving force behind our vehicle's precision. We design robust systems that navigate trajectories with centimeter-level accuracy—smoother and more reliably than a human driver—across a vast range of real-world conditions.

About the Role

We are seeking a highly skilled software engineer to advance Avride's core Control System. In this role, you will architect sophisticated control systems using Model Predictive Control (MPC) and identify the dynamic parameters of our vehicles.

What You'll Do

• Design, implement, and optimize cutting-edge control systems in modern C++ (C++17/20).
• Develop and refine robust, high-precision solutions for trajectory tracking.
• Analyze and iterate on system performance using real-world vehicle data.
• Collaborate closely with engineers from our Planning and Hardware teams to build a cohesive and reliable self-driving system.
• Write clean, maintainable, and optimized production-quality code.
• Profile and optimize algorithms to meet real-time performance constraints.

What You'll Need

• 3+ years of professional software engineering experience.
• Expertise in modern C++.
• Deep understanding of algorithms, data structures, and software design patterns.
• Hands on experience on data analysis and basic statistical methods.
• Exceptional communication and collaboration skills, with a focus on delivering results and driving projects to completion.

Nice to Have

• Direct experience in robotics, with a strong grasp of Optimization, MPC, and system dynamics.
• Digital signal processing techniques to analyse real-word sensor data.
• Advanced knowledge of mathematics (optimization, probability, mechanics) and a proven ability to translate complex theories into production-ready algorithms.
• Relevant publications or achievements in hackathons and programming contests.
• A passion for staying at the forefront of the field, actively seeking and implementing state-of-the-art ideas to push our performance beyond the current horizon.