F22 LABS - Senior Machine Learning Engineer - Computer Vision

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

• 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

• 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

(ref:hirist.tech)