Overview
We are seeking a highly skilled and proactive AI Research & Development Engineer to lead the exploration, automation, and orchestration of cutting-edge Generative AI tools. In this role, you will research emerging AI models, integrate multiple AI workflows, and develop scalable synthetic data pipelines for deepfake detection. Your responsibilities will span AI tool benchmarking, synthetic dataset generation, data orchestration, and automation, ensuring seamless processing and analysis of AI-generated content. You will work with Python, SQL, AWS, PySpark, and other advanced tools to enhance model accuracy, optimize cloud-based processing, and improve deepfake classifiers. This role requires strong project management skills, the ability to work independently, and a passion for staying at the forefront of AI innovation. You will collaborate with a diverse international team, contributing to the development of trust and safety technologies that impact the industry globally.
Key responsibilities
- Identify, evaluate, and benchmark state-of-the-art Generative AI tools (e.g., OpenAI, Stability AI, RunwayML, ElevenLabs, Pika Labs, and other open-source tools).
- Stay updated with emerging AI models in video synthesis, face manipulation, deepfake detection, and text-to-video technologies.
- Experiment with new model architectures, APIs, and frameworks for scalable content generation.
- 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.
- 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.
- Analyze video synthesis outputs to assess realism, quality, and AI model bias.
- Conduct data-driven experiments to measure the effectiveness of generated datasets.
Required experience
- At least 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
- 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
Bonus points
- Independent: The ideal candidate should be able to work independently with minimal supervision, efficiently manage their workload, and make 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 staying current with industry trends
- Candidates with experience in using Databricks for data engineering and analysis will have an advantage. Candidates who’ve served in the intelligence force as malware / cyber security analysts have an advantage.
- Candidates who’ve worked in a diverse team of professionals from different nationalities
To apply
Send your CV, a snappy cover letter which highlights your expertise, skills and experience and any relevant links/attachments to your work.
Have questions?Write to us