Autopilot Quality Analyst

Autopilot Quality Analyst

The key aspects defining the quality of an autonomous vehicle are safety, comfort, and efficiency. A thorough analysis of the technology's performance is a crucial step towards the widespread adoption of autonomous transport.

Quality Analysis specialists work together with research and engineering teams at every stage of software development to ensure the autopilot technology meets high safety standards, regulations, and driving requirements.

Various approaches are used to assess quality. In addition to collecting data from real roads, we also create synthetic driving scenarios using simulation technology. This allows us to analyze the vehicle's behavior in a virtual environment, quickly identify and compare how the car's behavior changes when driving in various weather conditions and road situations.

About the team

• The autonomous transport team consists of 600 people and is growing very rapidly.
• You will work with ML developers, software quality engineers, and data labeling teams.
• Your direct colleagues are five autopilot quality analysts for passenger and freight transport.
• The team lead is Anton Marzen, an engineer and analyst with 10 years of experience in data-based products, author of the Product Science Telegram channel.
• Tasks come from the CTO, Head of QA, and ML leads, and are decomposed and prioritized together with the team lead.

What tasks await you

Developing approaches for evaluating autonomous driving systems You will create methodologies and criteria for evaluating autopilot algorithms on real roads and in a virtual environment.

Creating and developing a quality metrics system You will develop indicators that will allow for a more accurate assessment of the comfort, efficiency, and reliability of autonomous driving systems.

Developing new statistical methods for analysis and evaluation You will create data analysis methods — for example, combining real and synthetic data — to improve the accuracy of assessments and trend analysis.

Formulating and solving complex problems You will work on complex tasks related to autonomous driving, including structuring the subject area, data analysis, and drawing conclusions and recommendations based on the results obtained.

Assisting in decision-making You will support machine learning specialists, developers, and quality engineers in choosing optimal solutions based on data.

We expect you to

• Be proficient in SQL and Python Data Science Stack
• Have worked on CV/ML-based projects
• Have worked with big data processing ecosystems, such as Hadoop
• Have confident knowledge of statistics for hypothesis testing and conducting experiments
• Have designed data models and metrics architecture
• Be able to study and analyze specialized literature and scientific papers in English