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Senior Data Scientist ( Kernel Optimisation & Inference Engineer)

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Onsite

Senior Data Scientist ( Kernel Optimisation & Inference Engineer)

eka.care

Senior Data Scientist ( Kernel Optimisation & Inference Engineer)

Skills

Google Cloud PlatformDeep LearningPythonData ScienceJavaPyTorchTensorFlowRData AnalysisMachine LearningAWS

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

11 August 2026

What they need


We are looking for a highly skilled Senior Data Scientist with expertise in Kernel Optimization Inference Engineering to join our team at Eka.care. The ideal candidate will have a strong background in data science and excellent problem-solving skills.

Roles and Responsibility

  • Design and develop scalable machine learning models using kernel optimization techniques.

  • Collaborate with cross-functional teams to integrate data science solutions into existing systems.

  • Develop and implement predictive analytics models to drive business growth.

  • Conduct exploratory data analysis and feature engineering to identify trends and patterns.

  • Optimize model performance using hyperparameter tuning and other techniques.

  • Work closely with stakeholders to understand business problems and develop solutions.

Job Requirements

  • Strong proficiency in programming languages such as Python, R, or Java.

  • Experience with deep learning frameworks such as TensorFlow or PyTorch.

  • Excellent understanding of statistical concepts and machine learning algorithms.

  • Strong analytical and problem-solving skills with attention to detail.

  • Ability to work collaboratively in a team environment and communicate complex ideas effectively.

  • Experience with cloud-based platforms such as AWS or GCP is a plus.

Disclaimer: This job description has been sourced from a public domain and may have been modified by Naukri.com to improve clarity for our users. We encourage job seekers to verify all details directly with the employer via their official channels before applying.

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