Research & Development of GenAI Tools
Identify, evaluate, and benchmark state-of-the-art Generative AI tools (e.g., OpenAI, Stability AI, RunwayML, ElevenLabs, Pika Labs, other open source).
Stay updated with emerging AI models in video synthesis, face manipulation, deep fake detection, and text-to-video technologies.
Experiment with new model architectures, APIs, and frameworks for scalable content generation.
2. Orchestration & Automation
Design automated workflows for orchestrating multiple GenAI tools to generate videos at scale.
Develop pipelines integrating text, audio, and video generation models (e.g., combining LLMs with synthetic media tools).
Optimize GPU/Cloud-based processing for efficient batch generation of synthetic datasets.
Ensure seamless data pipeline integration for AI/ML model training.
3. Synthetic Data Generation for Deep Fake Classification
Generate large-scale synthetic deep fake datasets using various AI-driven tools.
Develop procedural rules to create diverse video content, mimicking real-world deep fake patterns.
Implement labeling and annotation workflows to tag deep fake and real video content accurately.
Work with ML engineers to improve dataset quality for deep fake classifiers.
4. Data Analysis & Performance Monitoring
Analyze video synthesis outputs to assess realism, quality, and AI model bias.
Conduct data-driven experiments to measure the effectiveness of generated datasets.
Develop dashboards, reports, and insights to track synthetic data performance.
Identify and troubleshoot model weaknesses and anomalies in deep fake detection.
5. Data Feed Development
Design and implement data feeds from external sources, ensuring accuracy, reliability, and efficiency.
Develop automated processes for data collection and ingestion, utilizing appropriate tools and technologies.
6. Data Scraping and Analysis
Conduct data scraping from diverse external sources to gather relevant information.
Perform heuristic analysis and data exploration to derive insights for better prioritization of tasks and projects.
7. Collaboration and Communication:
Work effectively with a diverse team of multicultural freelancers, fostering a collaborative and inclusive work environment.
Maintain clear and open communication channels to facilitate seamless coordination and feedback exchange.
דרישות:
1-3 years of project management experience: The role demands excellent project management capabilities, including planning, execution, and tracking project progress. The ability to manage timelines, resources, and stakeholder expectations is crucial.
Proficient in Python programming: The ultimate person must have extensive experience in Python, capable of writing efficient, clean, and well-documented code.
Expertise in SQL: applicants should possess strong SQL skills, able to design, query, and manage databases effectively, with a focus on data manipulation and optimization.
Experience with data processing libraries: Candidates should have practical experience with PySpark and/or Pandas for data processing and analysis. Proficiency in handling large datasets and performing complex data transformations is essential.
Familiarity with AWS Services: Knowledge of AWS cloud services is required, including but not limited to EC2, S3, Lambda.
Working constantly with GenAI tools, and implemented integration and orchestration projects with multiple media formats
Soft Skills:
Independent: The ideal candidate should be able to work independently, with minimal supervision, efficiently managing their workload and making informed decisions.
Proactive: We are looking for individuals who are proactive in nature, always looking for ways to improve processes, solve problems before they escalate, and take initiative in their work.
Self-Learner: The ability to learn new technologies and methodologies quickly and effectively is essential. Candidates should demonstrate a strong capacity for self-directed learning and stay המשרה מיועדת לנשים ולגברים כאחד.
