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Data Scientist

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Onsite

Data Scientist

Infinityquest It Services

Data Scientist

Skills

SQL QueriesData EngineeringPythonPyTorchTensorFlowData AnalysisMachine LearningAINLP / Natural Language ProcessingPySpark

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹50,000 – ₹200,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

4 September 2026

What they need


Senior AI/ML Engineer/Data scientist with strong expertise in Python programming, Machine Learning, and Data Engineering. The ideal candidate will design, develop, and deploy scalable AI/ML solutions leveraging the Palantir platform, while ensuring robust data pipelines and infrastructure to support advanced analytics and predictive modeling.

Key Skills & Responsibilities

  1. Designing, build, and optimize machine learning models for classification, regression & NLP
  2. Experience in model training, validation, and deployment pipelines using frameworks like TensorFlow, PyTorch, or Scikit-learn.
  3. Excellent proficiency with Python (Good to have experience with PySpark as well)
  4. Prompt Engineering
  5. Have build Generative AI applications using tools and frameworks like LangChain or another libraries
  6. Monitor model performance and retrain models as needed.
  7. Experience building Agentic AI applications will be a plus
  8. Understanding of MlOps best practices
  • Collaboration

  • • Work closely with data scientists, software engineers, and business stakeholders to translate requirements into technical solutions.

  • Mentor junior engineers and contribute to technical design reviews.

  • Innovation

  • Stay updated with the latest advancements in AI/ML and data engineering technologies.

  • Propose and implement innovative solutions to improve business processes.

Good to have

  • Learning/work experience with Palantir platform and awareness with its AIP features
  • Develop and maintain ETL pipelines for large-scale data ingestion and transformation.
  • Work with structured and unstructured data from multiple sources (APIs, databases, streaming platforms).
  • Optimize data storage and retrieval using SQL/NoSQL databases and cloud data warehouses.

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