As a Software Engineer at Imagry, your day-to-day responsibilities will vary depending on your specialization, but they center around building a reliable, real-time autonomous driving stack.

• Design and Implementation – You will write clean, maintainable, and highly optimized code in C++ or Python. You will be responsible for taking algorithmic concepts from research papers and implementing them as robust software modules that run on the vehicle.
• Cross-Functional Collaboration – Autonomous driving is a highly integrated problem. You will collaborate daily with adjacent teams. For example, a Motion Planning Engineer must work closely with a Perception Engineer to understand the noise characteristics of object tracks, while a C++ Developer will help both teams optimize their code for the target hardware.
• Testing, Simulation, and Validation – You will not just write code and hand it off. You will write extensive unit and integration tests, validate your algorithms in high-fidelity simulation environments, and analyze log data from real-world test vehicle drives to debug complex system behaviors.
• Performance Profiling – You will continuously profile the software stack to identify latency bottlenecks, memory leaks, and CPU/GPU utilization spikes, ensuring the system consistently meets real-time execution deadlines.

To be competitive for a Software Engineer role at Imagry, you must possess a strong foundation in computer science or robotics, coupled with practical, hands-on development experience.

• Must-have skills – Proficient in modern C++ (C++14 or newer) or Python, with a strong grasp of data structures, algorithms, and software design patterns. For AI roles, deep familiarity with PyTorch or TensorFlow is required. Excellent linear algebra and calculus fundamentals are essential across all teams.
• Nice-to-have skills – Experience with ROS/ROS2 (Robot Operating System), CUDA programming, TensorRT, or development on embedded systems (e.g., NVIDIA Jetson platform). Prior experience in the autonomous vehicle, robotics, or aerospace industries is highly valued.
• Experience levels – Typically, mid-level roles require 3+ years of relevant industry experience, while Senior and Staff roles require 6+ years of experience, along with a track record of leading complex technical projects from concept to deployment.
• Soft skills – Strong communication skills, a proactive attitude toward problem-solving, comfort with ambiguity, and the ability to give and receive constructive, direct technical feedback.

Q: How difficult is the interview process at Imagry? A: The process is generally rated as difficult and highly technical. The engineering team places a strong emphasis on fundamental understanding. You cannot rely on buzzwords or surface-level knowledge; you must be prepared to write code on the whiteboard or in a shared editor and explain the low-level implications of your implementation.

Q: What is the typical timeline from the first screen to an offer? A: The timeline can be highly variable. Some candidates experience a very fast, streamlined process ("straight to the point") that concludes in a couple of weeks. Others, particularly those undergoing multiple in-person rounds or interviewing for highly senior roles, may experience a process that takes several weeks.

Q: How does Imagry's mapless approach change the engineering challenges compared to other AV companies? A: It shifts a massive amount of complexity onto the real-time perception and online planning systems. Since our vehicles cannot rely on pre-mapped lane lines or traffic light locations, our vision networks must interpret the environment dynamically, and our planners must make decisions with a higher degree of environmental uncertainty.

Q: Is there a hybrid or remote work option for these roles? A: While some initial stages are conducted online, Imagry highly values in-person collaboration. Hiring managers frequently utilize face-to-face meetings during the interview process to build rapport. Most engineering roles require a consistent physical presence at our offices in Haifa, Israel or San Jose, CA.

• Demonstrate Seniority through Ownership: If you are interviewing for a senior role, don't wait for the interviewer to prompt you about edge cases, testing, or system constraints. Proactively discuss how you would structure your code for production, write unit tests, and monitor the performance of your system in the field.
• Master Your Tools: Be ready to write syntactically correct code without relying on IDE auto-complete. If you are a C++ candidate, know your standard library (STL) inside and out. If you are a deep learning candidate, be prepared to write custom training loops or loss functions on a whiteboard.

• Understand the Hardware Constraints: Autonomous driving software does not run in an infinite-resource cloud environment. Always frame your technical answers with hardware constraints in mind. Mentioning CPU/GPU memory limits, latency budgets, and thermal throttling shows that you understand the realities of deploying robotics software in the physical world.

• Ask Deep, Fundamental Questions: At the end of your interviews, use your Q&A time to ask highly technical questions. Inquire about how they handle specific edge cases, how they structure their simulation pipelines, or how they manage hardware-in-the-loop (HIL) testing. This demonstrates that you are already thinking like an Imagry engineer.

A Software Engineer position at Imagry is an exceptional opportunity to tackle one of the most challenging and impactful engineering problems of our generation: mapless autonomous driving. By eliminating the crutch of HD mapping, Imagry engineers are building a highly scalable, adaptable AI brain that can drive anywhere in the world. This bold technical vision requires a team of highly dedicated, technically rigorous, and collaborative engineers.

To succeed in this interview loop, focus your preparation on core computer science and engineering fundamentals. Ensure your coding skills are sharp, your understanding of systems or deep learning mathematics is rock-solid, and you can articulate your technical decisions clearly under pressure. Approach the process with a collaborative mindset, and be prepared to engage deeply with a highly professional engineering team that values technical truth and execution.

For additional resources, detailed community insights, and comprehensive preparation tools tailored to top-tier technology companies, you can explore more interview experiences and guides on Dataford.

The salary ranges provided represent the base compensation for various engineering specializations at our San Jose, CA office. When evaluating an offer or preparing for salary discussions, keep in mind that total compensation packages may also include equity, performance bonuses, and comprehensive benefits. Your specific offer will depend on your depth of experience, technical domain expertise, and the results of your interview evaluation.