Senior Data Scientist (Transformers/Deep Learning)

Job Summary: As a Senior Data scientist, you will lead the research, analysis, and development of advanced video generation models to enhance Akaike's current and prospective content production. This initiative aims to achieve quantifiable improvements in user engagement, satisfaction, and retention, driven by data-driven innovations.

About the team: We’re an agile, fast-moving team, focused on turning bold ideas into impactful products. From rapid prototyping of new concepts to building scalable platforms that power future growth, we thrive on experimentation and innovation.

Our platform highlights creators and their narratives by giving them AI-powered systems using advanced machine learning and multimedia pipelines.

As part of this team, you’ll work at the intersection of creativity and technology - building end-to-end experiences, experimenting with emerging tech, and shaping the future of entertainment content.

Key responsibilities:

• Design, prototype, and refine deep learning models for text-to-video and image-to-video generation using cutting-edge techniques in generative AI (e.g., diffusion models, transformers, temporal GANs)
• Collaborate with 3rd-party AI vendors to evaluate their capabilities, run quality benchmarks, and drive technical integration where applicable
• Lead the creation of in-house solutions to augment 3rd-party offerings, with a focus on improving video quality, generation time, and content relevance
• Develop robust pipelines for dataset curation, preprocessing, training, and model evaluation, including automated visual, temporal, and semantic quality metrics
• Work closely with product managers, engineering teams, and senior leadership to define use cases, set priorities, and bring production-grade AI systems to life
• Run A/B tests, iterate based on performance feedback, and ensure alignment with product experience goals and creative quality standards
• Stay ahead of the curve in the fast-moving GenAI space; guide strategy, share insights internally, and represent the team in technical forums as needed

Skills and attributes for success:

• Strong understanding of LLMs, with hands-on experience in fine-tuning, prompt engineering, and evaluating foundation models for applied use-cases for multimodal generation
• Proven experience with deep learning architectures for generative tasks (e.g., diffusion models, transformers, GANs)
• Good understanding of computer vision, natural language processing, and multimodal learning
• Experience with training large-scale models, transfer learning, and fine-tuning on custom datasets
• Familiarity with ML evaluation techniques, including perceptual quality metrics and user-in-the-loop testing
• Knowledge of model deployment and performance tuning in production environments
• Hands-on experience building and optimizing text-to-video, image-to-video, or similar generative pipelines
• Hands-on experience with Python, SQL, and TensorFlow/PyTorch for implementing and evaluating algorithms
• Excellent communication skills; able to present complex concepts clearly to technical and non-technical stakeholders
• Experience with experimental design and A/B testing methodologies

Preferred education and experience:

Bachelor's in Computer Science, Statistics, Mathematics, or related quantitative field with 4+ years of hands-on experience in applied machine learning or deep learning, with at least 2 years working on generative AI or related video technologies.