Senior Software Engineer - Neural Simulation
$60k - $300k • Sunnyvale • FullTime
Posted 9h ago
About the job
Applied Intuition is seeking a Senior Software Engineer to join the Neural Simulation team. This role involves building the core systems for a state-of-the-art product that transforms real-world driving data into high-fidelity simulation environments. You will design and develop systems for large-scale reconstruction, synthetic data generation, and log augmentation, as well as ML pipelines for training and validating autonomy systems. The position requires working on highly distributed systems that process real-world data into simulation environments and generate labeled data at scale, emphasizing careful system design across compute, storage, and data pipelines. This is an ideal opportunity for engineers passionate about the intersection of large-scale distributed systems and machine learning, aiming to scale a cutting-edge product and address complex data and platform challenges in Physical AI.
Responsibilities
- Design and build scalable closed-loop simulation systems using Neural Reconstruction.
- Architect systems for processing and managing large-scale data.
- Develop infrastructure for ML workflows, including training, evaluation, validation, and inference pipelines.
- Design and optimize storage solutions for various data types (structured, unstructured, multimodal).
- Improve the reliability, observability, and performance of distributed services.
- Collaborate with cross-functional teams (Infra, Autonomy, Research, Product) to deliver end-to-end solutions.
- Take ownership of critical systems and influence architectural and product decisions.
Requirements
- 5+ years of experience shipping complex, large-scale software.
- Bachelor's degree in computer science, computer engineering, or equivalent practical experience.
- Proven track record in designing, building, and operating scalable distributed systems, data pipelines, and data storage solutions (SQL, NoSQL, vector databases, data lakes).
- Experience with cloud platforms (AWS, GCP, or Azure).
- Experience with containerized systems (Docker, Kubernetes).
- Experience with backend development in languages like Python and Go.
- Strong system design and problem-solving skills.