Data Scientist

2 weeks ago

Bengaluru Karnataka, India Oracle Full time

At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.

In the OCI AI Science org, we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. As a Data Scientist III, you will play a key role in developing large-scale datasets leveraging Machine learning and Generative AI to train Generative AI models. You will work closely with scientists, engineers, and product teams to design benchmarking frameworks, ensure the highest standards of model and data quality.

**Key Responsibilities**:

- Design and develop large-scale datasets to power generative AI models in multimodal domains (e.g., text, vision, speech), with a focus on synthetic data creation.
- Build robust pipelines and tooling for data acquisition, cleaning, transformation, and quality assurance to support model training and evaluation.
- Research, implement, and adapt cutting-edge techniques (e.g., fine-tuning, RLHF, data augmentation) to align generative models with domain-specific needs.
- Curate and annotate datasets, ensuring diversity, representativeness, and compliance with responsible AI practices.
- Evaluate open-source and research models, integrating best practices into data generation workflows.
- Collaborate with engineering teams to ensure datasets and synthetic data pipelines are scalable, reliable, and production ready.
- Develop metrics and benchmarking frameworks to assess data quality, model alignment, and downstream impact across modalities.

**Qualification and Skills**:

- Bachelors or Master’s in Computer Science, Data Science, AI/ML, or related field with 3+ years of industry experience.
- Proficiency in Python and solid foundation in applied ML methods.
- Proficiency with Pytorch, Torchvision, OpenCV, and similar, as well as building and deploying DNN models in production.
- Experience building large-scale data pipelines for acquisition, cleaning, augmentation, and validation.
- Ability to evaluate datasets for distribution, diversity, anomalies and fairness to assess overall quality and suitability for generative AI.
- Experience with Computer Vision, NLP, Transformers, Large Language Models, Generative AI, optimizations around LLM training and serving. Experience with multimodal models a bonus.
- Proven track record of delivering scalable, data-centric ML solutions.

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