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# Sr. Software Engineer

- **Company:** HERE
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $130,000.0 - $140,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Geographic Information Systems, Application Programming Interfaces (APIs), Systems Engineering, Automation of Tests, Big Data, C++ (Programming Language), Cloud Computing, Continuous Integration, Data Transformation, Python (Programming Language), Machine Learning, Spatial Data Infrastructures, Data Streaming, Backend, Api Design, Golang, Data Generation
- **Published:** August 31, 2026
- **Apply:** https://www.disabledperson.com/jobs/74699568-sr-software-engineer

## About the Role

Building useful simulation is a systems problem as much as a modeling problem. Scenarios must be represented consistently, data must move efficiently, experiments must be reproducible and results must be measurable at scale., You are a strong systems engineer who is energized by simulation, spatial data and software that models real-world behavior.

 * Strong software-engineering experience in Python, C++, Java, Go or another relevant systems/backend language.
 * Experience building distributed services, data-intensive applications or simulation infrastructure.
 * Strong knowledge of API design, data modeling, testing and production operations.
 * Experience with cloud infrastructure, containers and CI/CD practices.
 * Ability to reason about complex data flows, performance bottlenecks and reproducibility.
 * Strong collaboration skills across applied science, simulation and product engineering.

It would be great if you also bring

 * Experience with CARLA, NVIDIA DRIVE Sim, OpenSCENARIO, OpenDRIVE or related tooling.
 * Experience with geospatial data, trajectories, sensor data or 3D environments.
 * Familiarity with synthetic-data generation or ML training and evaluation loops.
 * Experience with GPU-backed or large-scale batch workloads.

## Description

The work sits close to real technical outcomes: faster experimentation, broader scenario coverage and stronger confidence in systems designed for the physical world.
What will you do?

 * Build scalable services and pipelines for simulation scenarios, synthetic data, experiment execution and results analysis.
 * Develop APIs and data models that connect maps, trajectories, agents, environmental conditions and simulation outputs.
 * Integrate with simulation and scenario ecosystems while creating reliable internal abstractions.
 * Improve throughput, reproducibility, observability and performance across distributed workloads.
 * Create automated testing and validation for scenario definitions, data transformations and system behavior.
 * Partner with simulation experts, data scientists and ML engineers to translate research needs into durable software.
 * Own features from design through deployment, monitoring and iteration.


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