Collaborate with product and technology teams across the globe.
Conceptualize and co-develop innovative AI/ML solutions to address complex business challenges in the media space, contributing to a culture of rapid innovation.
Identify systematic frameworks for prompt engineering and evaluation, ensuring VLM outputs meet strict ground truth requirements.
Develop rigorous evaluation metrics (beyond standard accuracy) to validate model performance for temporal tasks.
Bridge experimentation and production through partnership with product and engineering teams, ensuring experimental models are aligned with business needs, optimized for inference and can be seamlessly integrated into our cloud platforms.
Establish and refine best practices for the application of generative and non-generative AI/ML techniques, ensuring optimal performance for both experimental and production use cases.
Develop statistical analyses to validate model performance and business impact.
Actively experiment with emerging techniques like PEFT (LoRA/QLoRA), Quantization, and Vector embeddings-based media retrieval.

Bachelor's in Computer Science, Data Science, or a related scientific/engineering field.
At least 7 years of relevant industry experience in data science.
Proficient in Python, and extensive experience with libraries such as Pandas, NumPy, and scikit-learn.
Hands-on experience with at least one major deep learning framework, such as PyTorch, and experience with LLM prompting and fine-tuning.
Solid understanding of the full lifecycle of a machine learning project, from data exploration and feature engineering to model deployment and monitoring.
Strong communication and presentation skills, with the ability to convey complex analytical findings to both technical and non-technical audiences.
Experience with cloud platforms, including storage, compute, and ML services such as AWS S3, Bedrock, EC2, and SageMaker or Databricks.

Lead Data Scientist, Content Intelligence

Key skills