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Role Overview : Machine Learning Engineer We are seeking a passionate and skilled Senior Machine Learning Engineer to join our ML team, focused on advancing our work in object detection, image segmentation, and 3D reconstruction. The ideal candidate will bring strong technical capabilities, a proactive R&D mindset, and an eagerness to stay updated with the latest advancements in computer vision. This role involves working on cutting-edge CV problems, understanding and improving complex codebases, and contributing meaningfully to our mission. Experience in the construction domain or real-world deployment scenarios is a strong plus. Key Responsibilities Design and implement models for object detection, semantic/instance segmentation, and 3D reconstruction Analyze and debug large-scale computer vision pipelines Collaborate with cross-functional teams to integrate ML models into production systems Conduct research and experiments to evaluate emerging methods and improve current workflows Understand and enhance existing codebases with clean, efficient, and maintainable code Communicate findings clearly and effectively across technical and non-technical teams What Were Looking For 7+ years of hands-on experience in Machine Learning and Computer Vision Proficiency in Python and libraries such as PyTorch, TensorFlow, OpenCV, NumPy etc. Decent experience with object detection models and segmentation techniques. Strong understanding of 3D vision techniques (SfM, MVS, SLAM, COLMAP, etc.) Excellent debugging, problem-solving, and code comprehension skills Positive attitude, curiosity-driven approach, and strong willingness to learn and adapt Preferred Qualifications Exposure to construction technology or domain-specific datasets (e.g., aerial/spherical/360 imagery) Experience with large-scale data processing and pipeline optimization Publications, GitHub contributions, or open-source involvement in computer vision projects Experience working in collaborative environments using version control (e.g., Git) and code review processes .
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.