Senior Machine Learning Engineer

Oracle India Private Limited; Bengaluru; On-site; INR 3,500,000 - 5,500,000; Full time

Benefits offered by this job

Flexible medical benefits

Life insurance

Retirement options

Volunteer programs

Job summary

Oracle India Private Limited seeks a Senior Machine Learning Engineer to design and build data-centric GenAI methods for synthetic data generation and multimodal data curation. You will develop pipelines for text, speech, vision, and multimodal GenAI use cases, including controllable generation and safety checks.

You'll evaluate research papers, implement practical techniques in real-world systems, and lead production ML workflows from data acquisition to model evaluation, ensuring scalable,

Qualifications

• Ph.D., Master's degree, or equivalent practical experience in CS/AI/ML or related field.
• 5+ years with Master's, or 3+ years with Ph.D., applying ML to real-world problems.
• Strong Python programming and production ML experience.
• Hands-on with PyTorch and deep-learning stacks; Hugging Face/LLMs/VLMs/diffusion models favored.
• Experience with data-centric GenAI methods and data quality/augmentation.

Responsibilities

• Lead data-centric GenAI solutions for synthetic data generation and multimodal data curation.
• Develop and evaluate synthetic-data pipelines for text, speech, vision, and multimodal GenAI use cases.
• Create evaluation frameworks linking data quality to model performance.
• Prototype and implement modern GenAI techniques in production systems.
• Build scalable ML pipelines for data acquisition, cleaning, labeling, training, and evaluation.
• Translate research into practical systems to improve data quality and AI outcomes.
• Collaborate with product, infra, and domain teams to define data requirements and delivery plans.
• Oversee full development lifecycle from research to production support.

Skills

Python programming

ML deployment

GenAI

Experiment design

Statistics

Model monitoring

Communication

Data pipelines

Cloud computing

Education

PhD or Master's in CS/AI/ML related field

Tools

PyTorch

Hugging Face

LLMs

VLMs

Diffusion models

Job description

Senior Machine Learning Engineer

Qualifications

Ph.D., Master's degree, or equivalent practical experience in Computer Science, Artificial Intelligence, Machine Learning, Operations Research, Statistics, or a related technical field.

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; experience with Hugging Face, LLMs, VLMs, diffusion models, or multimodal models is strongly preferred.

Experience with data-centric AI or GenAI methods, such as 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.

Ability to evaluate research papers, identify practical value, and implement useful techniques in real-world systems.

Experience building scalable data or ML pipelines using distributed compute, cloud storage, batch processing, or workflow orchestration.

Strong written and verbal communication skills, including experience preparing technical proposals, design documents, experiment reports, and stakeholder presentations.

Description

Design and build data-centric Generative AI methods for synthetic data generation, multimodal data curation, augmentation, filtering, deduplication, and data-quality assessment.

Develop and evaluate synthetic-data pipelines for text, speech, vision, and multimodal GenAI use cases, including controllable generation, provenance tracking, safety checks, and domain adaptation.

Build evaluation frameworks that connect data quality with downstream model performance through benchmark design, ablation studies, error analysis, and model-feedback loops.

Research, prototype, and implement modern generative AI techniques, including LLM/VLM-based data generation, fine-tuning, instruction tuning, preference optimization, and model-based data labeling.

Build scalable data and ML pipelines for data acquisition, cleaning, transformation, metadata extraction, embedding generation, labeling, training, and evaluation.

Develop production-quality code for batch and real-time ML workflows, including model inference, feature processing, data validation, monitoring, and operational automation.

Translate research papers and emerging GenAI techniques into practical systems that improve data quality, model performance, and customer-facing AI outcomes.

Partner with modeling, product, infrastructure, and domain teams to define data requirements, quality standards, evaluation criteria, and delivery plans.

Operate across the full development lifecycle, including research, prototyping, experimentation, productionization, testing, CI/CD, monitoring, runbooks, and production support.

Responsibilities

Lead the design, implementation, and continuous improvement of data-centric GenAI solutions and synthetic-data capabilities.

Define and maintain 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.

Collaborate with cross-functional teams to prioritize use cases, align on technical requirements, and deliver scalable production solutions.

Contribute to technical designs, experiment reports, documentation, and stakeholder presentations.

Support production deployments by establishing monitoring, quality controls, operational processes, and troubleshooting procedures.

Stay current with relevant research and industry developments, assessing and applying techniques with practical business value.

Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life‑saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all.

Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives.

True innovation starts when everyone is empowered to contribute.

That's why we're committed to growing a workforce that promotes opportunities for all with competitive benefits that support our people with flexible medical, life insurance, and retirement options.

We also encourage employees to give back to their communities through our volunteer programs.

We're committed to including people with disabilities at all stages of the employment process.

If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing [e-mail] or by calling 1-888-404-2494 in the United States.

Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law.

Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

Experience Level Senior Level