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Ray Business Technologies (A CMMI Level 3 Company) · Hyderabad, Telangana, India

Data Scientist- 5Plus Years ( Fine Tuning)

entry_levelfull timePosted Aug 13
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pythonmicroservicestransformersazureetldata-sciencefine-tuningartificial-intelligencedata-governancecomputer-visionsystem-designa/b-testing

AI/ML Engineer (5+ Years)

We’re building AI systems that convert unstructured visual data into structured, usable outputs that power real-world workflows.

This role focuses on solving messy, high-variability problems and delivering reliable systems in production, not just training models in isolation.

What You’ll Do

- Build and improve end-to-end AI/ML pipelines (input ? preprocessing ? inference ? structured output)

- Work with noisy, inconsistent datasets and drive improvements in data quality and model performance

- Develop preprocessing pipelines (e.g., normalization, transformations, input standardization)

- Run experiments, tune models, and evaluate trade-offs across accuracy, latency, and cost

- Collaborate with engineering teams to productionize models (APIs, batch/real-time systems)

What We’re Looking For

- 5+ years of hands-on experience in ML/AI with exposure to computer vision

- Strong Python skills with production-quality coding practices

- Solid understanding of microservices and system design.

- Experience building and deploying ML systems beyond experimentation

- Experience working on systems that extract or process information from complex visual inputs (e.g., documents, forms, or similar structured outputs)

- Strong understanding of neural network architectures (e.g., CNNs, Transformers, sequence models) and their real-world trade-offs.

- Ability to:

- Select appropriate approaches based on problem constraints

- Fine-tune and optimize models for performance and reliability

- Debug model behavior and failure cases in production

- Strong understanding of evaluation metrics, error analysis, and model limitations

Good to Have

- Experience with cloud environments (e.g., Azure or similar)

- Familiarity with scalable data pipelines, containerization, or distributed systems

- Exposure to multi-modal systems (vision + text)

What We Don’t Want

- Only academic or demo project experience

- Over-reliance on plug-and-play APIs without understanding internals

- Inability to explain past work end-to-end (data ? model ? output ? impact)

- Profiles focused only on generic image classification or object detection use cases without real-world deployment experience

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