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As a working student in Software Engineering, you support the annotation and quality assurance of training data as well as the structured management of our datasets. You also contribute to the definition and evaluation of KPIs for assessing our models and assist in conducting end-to-end tests of the entire system pipeline. In addition, you research new approaches in the field of computer vision and compare them with existing solutions. Furthermore, you help to further develop our testing infrastructure and evaluation pipelines to ensure continuous quality assurance. What is your Day to Day Mission: Data Annotation & Dataset Management – Annotate and quality-check training data for object detection and end-to-end planner models, including bounding boxes, segmentation masks, and trajectory labels; maintain and version datasets to ensure consistency and traceability across model iterations KPI Definition & Model Evaluation – Design, implement, and continuously improve KPIs to monitor and benchmark the performance of ML models deployed on UAVs and UGVs, covering metrics such as detection auracy, latency, precision/recall, and robustness under real-world conditions End-to-End System Testing – Execute and automate end-to-end integration tests of the full perception and planning pipeline on target hardware (Nvidia Jetson), identifying bottlenecks and regressions across the entire system stack Research & Model Benchmarking – Independently investigate state-of-the-art publications and open-source models in computer vision, object detection, and autonomous systems; systematically compare novel approaches against our current solutions and document findings in a structured way Tooling & Test Infrastructure – Contribute to the development of testing scripts, evaluation pipelines, and CI-friendly unit tests to ensure continuous quality assurance of deployed ML components
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.