What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We’re searching for a Software Engineer II to join the Control Simulation team and help transform how we validate and improve the safety and performance of the Aurora Driver.

In this role, you will operate at the intersection of Machine Learning, Software Engineering, Data Science, and Vehicle Dynamics. You will contribute to the development of our next-generation data driven vehicle simulator, build data pipelines that source critical scenarios from our fleet and generate simulations from logs, and analyze data to prove the safety of our motion control software.

This is a high-impact role for an engineer who enjoys a mix of model development, infrastructure building, and data analysis.

In This Role You Will:

• Develop Vehicle Models: Help design and implement our next-generation differentiable vehicle dynamics simulator for controls V&V.
• Build Simulation Pipelines: Design and maintain the software pipelines required to generate "Sim-from-Log" scenarios. You will ensure that high-value on-road events are systematically converted into reproducible simulation tests.
• Implement Control Scenario Taxonomies & Curate Data: Build the data structures and algorithms to categorize complex control scenarios (e.g., maneuvers, environments) and use this framework to source balanced datasets from on-road logs, ensuring comprehensive ODD coverage for model training.

Required Qualifications:

• BS or MS in Computer Science, Robotics, Data Science, or a related engineering field.
• 2+ years of software engineering experience with a focus on data-intensive applications or machine learning.
• Strong proficiency in Python (including libraries like Pandas, NumPy, Scikit-learn).
• Hands-on experience with PyTorch or similar machine learning frameworks.
• Experience working with large datasets, SQL, and data processing pipelines.
• Strong analytical skills with the ability to translate complex data into actionable engineering insights.
• Background or interest in Control Theory or Vehicle Dynamics (understanding of kinematics, kinetics, and actuation).

Desirable Qualifications:

• Experience with machine learning or system identification for physics based-models.
• Familiarity with V&V methodologies, simulation frameworks, or log analysis tools.
• Experience building data visualization tools or dashboards to track software quality and coverage.
• Proficiency in C++ (necessary for integrating with on-vehicle or production codebases).

The base salary range for this position is $126,000-$181,000 per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

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About the Role:

As a Senior Data Scientist at Perpay, you will be a critical player in the day-to-day success of the business, supporting new and existing product initiatives through strong analytical skills and machine learning expertise. In addition, you will be responsible for helping shape the future of the data science team by developing processes and systems that scale with our rapidly growing business. This is an exciting opportunity to make a positive impact on the execution of Perpay’s mission and the lives of our customers. We are looking for someone who is passionate about all aspects of data science: from machine learning and exploratory data analysis to communication of results and real-time deployments. This crucial role will sit on our data science team and report to the Data Science Manager. If you’re looking for a collaborative team that you can bounce ideas off of and learn from, this is where you belong. We are about being curious, setting the standard and building good habits at Perpay.

Our greatest strength is our people and we’d love for you to be one of them!

Responsibilities:

• Drive the end-to-end completion of data science initiatives, collaborating with stakeholders from ideation through execution, ensuring projects deliver strong impact to our customer’s financial lives and the health of the business
• Proactively identify opportunities for the data science team to improve and expand Perpay’s business model using techniques from exploratory data analysis to machine learning models, leveraging subject matter expertise of Perpay’s business model
• Support the growth of the business by delivering scalable models and algorithms while maintaining and troubleshooting existing resources
• Deploy and maintain real-time model inference resources and infrastructure
• Deploy and maintain machine learning pipelines including batch processing and continuous training architecture
• Contribute to the cross-discipline adoption and responsible use of AI/LLM models and services at Perpay 
• Present results and analyses to the a wide range of audiences: from Perpay's leadership team to non-technical peers
• Contribute to defining standards and best practices concerning workflow and adoption of new technologies within the Data Science team
• Act as an informal mentor peers

What You’ll Bring:

• 5+ years of experience* and expertise applying machine learning techniques in industry
• 5+ years of experience* and expertise in producing data analysis, exploratory data analysis and data visualization in industry
• 5+ years of experience* and expertise in developing, deploying, maintaining real-time software (e.g. models exposed as APIs)
• 5+ years of experience* and expertise in Cloud compute infrastructure and best practices, including familiarity with tools such as terraform and Cloud Formation
• Bachelor's degree or higher in a quantitative/technical field (Mathematics, Statistics, Engineering, Chemistry, Physics)
• Excellent communication skills, across a range of audiences from technical to non-technical
• Strong business acumen, demonstrated through subject matter expertise in at least one industry
• Capable of managing projects “end to end” including managing project scope, timelines and workloads
• Advanced proficiency in Python and standard data science stack (e.g. scikit-learn, pandas, numpy, matplotlib, etc.)
• Team player: willingness and ability to establish strong working relationships not just within the data science team itself, but across the organization

*Internships not included

Nice to have:

• Expertise in multiple advanced machine learning methodologies: e.g. deep learning, probabilistic programming, mathematical optimization, etc.
• Deep familiarity in multiple advanced machine learning frameworks: e.g. tensorflow, pytorch, pymc, etc.
• Experience with scalable compute frameworks such as Spark or Polars
• Experience with deployment frameworks such as Kubernetes