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Youll join our existing AI engineer to divide and conquer the vision AI work as the company scales the perception layer that turns multi-spectral camera feeds into reliable detection, tracking, and decision support for operators in the field. Experience 37 years in computer vision, deep learning, or perception systems. Strong with PyTorch (or equivalent), classical CV (OpenCV), and edge model deployment (TensorRT, ONNX Runtime, or equivalent). Hands-on production experience with object detection and multi-target tracking. Image fusion, sensor calibration, or multi-sensor work is a plus. What You'll Do Build and ship production-grade vision models across our FX-Ground camera line: object detection, multi-target tracking, EO + thermal image fusion. Own a slice of the perception roadmap end-to-end training and evaluation through edge deployment on Jetson Orin hardware. Drive OpenCV-based tooling: ISP support, daynight fusion, sensor calibration. Classical CV that complements modern deep learning. Pick up cross-modal and RF fusion work as our radar partnership matures. Use our internal simulation pipeline (FX-Sim) as a first-class part of the model-development loop close the synthetic-to-real gap. Partner with our FPGA / image-acceleration work on hardware-accelerated pipelines, and with the operator-experience team on inference deployment paths. Get into the field debug models against real captures and drive the data flywheel that makes every deployment better than the last. Backgrounds That Fit Mid-level perception engineer from defence, robotics, autonomous driving, or surveillance industry Research-engineer profile from a strong CV lab (IIT / IIIT / equivalent) ML engineer with strong classical CV foundations alongside modern deep learning Email us with aCV and a short note on what youd want to build at FieldX. Use the subject line: Application for AI Engineer: Vision Models & Fusion .
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.