Clarity is an AI cybersecurity startup, protecting against deepfakes and new social engineering and phishing attack vectors accelerated by the rapid adoption of Generative AI. Its patent-pending technology detects AI manipulations in videos, images and audio and authenticates media with encrypted watermarking. Clarity's AI DeepFake Firewall integrates into new and existing workflows, and enables publishers and intelligence agencies to verify sensitive media, financial institutions to prevent fraud, and enterprises to filter manipulated media and create an AI-Safe media environment — in a market that's growing at ~40% CAGR. Founded by AI and Cyber experts from 8200, Stanford, and Israel’s National Security Council, it is advised and backed by global leaders in the AI and cyber industries.
Job Description
We are looking for a Senior Engineering Team Lead with a strong background in engineering ML infrastructure, computer vision and video/audio/image data analysis, to lead our ML Infrastructure and Platform Engineerings. The ideal candidate should have hands-on experience in dealing with media at scale and developing/deploying deep learning systems, data engineering, and software development along with strong management skills.
Responsibilities
Hands-on experience engineer in developing and deploying deep learning systems. Making decisions on architecture and design of the solutions
Strong Management skills. Managing the existing MLE and Platform team to grow the inference infrastructure and systems for deep learning research in computer vision, video and audio analysis. Manage the sprint tasks and day-to-day deliveries
Collaborating with the research team integrating and enhancing performance of ML models
Developing and implementing advanced processes for video data pre-processing, model training, testing, and evaluation within the context of deep learning applications
Continuously optimizing and enhancing our deep learning infrastructure Identifying and addressing bottlenecks and challenges within the deep learning research workflow
Work with CTO and Head of Product on the priorities and milestones
Requirements
6+ years professional experience of development ML infrastructure for inference and training of which at least 3 as team/group lead
Dealing with multi media at scale - video, audio and images
Proficient Python skills, encompassing Object-Oriented Design and asynchronous execution
BSc in Computer Science, Mathematics, Engineering or equivalent
Hands-on experience with deep learning Python frameworks, particularly PyTorch and TensorFlow
Proficiency with containerization technologies and Kubernetes
A solid foundation in distributed system architecture and frameworks, including Ray, MLFlow, Prefect
Strong teamwork skills and ability to collaborate and communicate effectively
Benefits
Prior experience in computer vision and video data analysis
Experience with Event-Driven and Data Pipeline architecture