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Metro location, mid-level ML role, and known startup brand increase applicant competition.
Role's embedded CV and fleet-focused ML requirements limit cross-industry transferability.
Explicit 4+ years, ML/CV expertise and strong Python/C++ requirement make shortlisting moderately strict.
Design, implement, and improve complex machine learning and computer vision systems for fleet safety and driver behavior analysis.
Prototype ML modules and optimize CV/ML algorithms for real-time performance on embedded AI dashcam platforms.
Collaborate cross-functionally and contribute to building scalable ML infrastructure including automated deployment, validation, and active learning pipelines.
Bachelor’s degree in Computer Science, Electrical Engineering, or related field; Master’s is a plus.
At least 4 years of experience in machine learning and/or data science.
Proficiency in Python or C++ programming languages.
Authorization to receive access to products and technology under U.S. Export Administration Regulations.
Experienced in deploying and optimizing ML models on embedded devices or embedded platforms.
Strong mathematical foundation in deep learning, machine learning, and optimization techniques.
Familiarity with cloud services (e.g. AWS), CI/CD, containerization (Docker, Kubernetes), and infrastructure-as-code (Terraform) is advantageous.