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Popular Data Scientist title and metro location increase competition, but niche computer-vision and embedded ML skills limit applicants.
Medium: core ML and computer-vision skills transfer across industries, but embedded/subsea domain expertise reduces portability.
High because the JD mandates many specific technical requirements and domain expertise (computer vision, embedded deployment, Azure, C++).
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Develop and deploy machine vision and computer vision algorithms for automation in operations involving inspection topside and subsea.
Lead full-cycle development of ML/DL solutions from conception to real-time implementation and integration into products, including data analytics and scalable infrastructure for model training and deployment.
Collaborate with software engineers and stakeholders to build product solutions, conduct research, and align technical strategy with business objectives.
Bachelor's or Master's degree in Computer Science, Software Engineering, or related field.
Proficiency in programming languages such as C, C++, Java, C#, and Python; strong coding skills required.
Experience with computer vision, image processing, Deep Learning, and ML algorithm implementation and deployment, including familiarity with OpenCV, PCL, CNN, and NVIDIA Jetson Board & Deep Stream Framework on Linux/Ubuntu.
Experience with cloud-based AI/ML services (specifically Azure), DevOps practices for ML code deployment, and UNIX (Solaris/Linux) and Windows platforms.
Able to independently lead development of advanced computer vision and machine learning algorithms with practical deployment in industrial products.
Experienced in building scalable ML infrastructure and integrating solutions in collaboration with software engineers and cross-functional teams.
Background combining strong mathematical/statistical modeling expertise with hands-on programming and operational deployment skills in AI/ML domains.