5 days ago
Bengaluru, IndiaSenior
Responsibilities
- Lead the design, implementation, and continuous improvement of data-centric GenAI and synthetic-data solutions.
- Define data-quality standards, evaluation metrics, and validation processes for GenAI datasets and models.
- Conduct experiments, analyze results, and recommend data or modeling improvements based on measurable outcomes.
- Build scalable data and ML pipelines for acquisition, cleaning, transformation, labeling, training, and evaluation.
- Develop production-quality batch and real-time ML workflows with inference, feature processing, validation, monitoring, and operational automation.
- Translate research papers and emerging GenAI techniques into practical production systems.
- Collaborate with modeling, product, infrastructure, and domain teams to define requirements and deliver solutions.
- Support production deployments through monitoring, quality controls, runbooks, troubleshooting, and operational processes.
Requirements
- Ph.D., Master's degree, or equivalent practical experience in Computer Science, Artificial Intelligence, Machine Learning, Operations Research, Statistics, or a related technical field.
- At least 5 years of relevant experience with a Master's degree or 3 years with a Ph.D. applying machine learning to real-world problems.
- Strong Python programming skills and experience building production-quality ML, GenAI, or data systems.
- Hands-on experience with PyTorch and modern deep-learning stacks.
- Preferred experience with Hugging Face, LLMs, VLMs, diffusion models, or multimodal models.
- Experience with data-centric AI or GenAI methods including synthetic-data generation, data-quality measurement, dataset curation, weak supervision, model-based labeling, active learning, deduplication, or data augmentation.
- Experience designing experiments and interpreting results through statistical analysis, ablation studies, benchmark evaluation, and error analysis.
- Strong understanding of model training, inference, evaluation, and production monitoring.
- Experience building scalable data or ML pipelines using distributed compute, cloud storage, batch processing, or workflow orchestration.
- Ability to evaluate research papers and implement useful techniques in real-world systems.
- Strong written and verbal communication skills, including technical proposals, design documents, experiment reports, and stakeholder presentations.
Benefits
- Competitive benefits including flexible medical, life insurance, and retirement options.
- Volunteer programs supporting employee community involvement.
- Accessibility assistance and accommodations are available throughout the employment process.
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About Oracle
Oracle builds database technology, enterprise applications, and Oracle Cloud Infrastructure for companies and governments. Its business spans cloud subscriptions, software licenses, and support services across ERP, HCM, CX, and industry suites, plus NetSuite. Founded in 1977 and headquartered in Austin, Texas, Oracle is a public company traded on the NYSE and serves global customers migrating and running critical workloads in its cloud.