Data Scientist - BLR

Celebal Technologies
Department Icon Data Science Analytics & Machine Learning
Posted: 2 days ago
4-9 years
Bengaluru
Data Science Analytics & Machine Learning
work from office
Full Time
Closes 9 Jan 2027
Posted: 2 days ago
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Job Description

  • Senior Data Scientist
  • About Us:
  • Celebal Technologies is a leading Solution Service company that provide Services the field of Data
  • Science, Big Data, Enterprise Cloud & Automation. We are at the forefront of leveraging cutting-
  • edge technologies to drive innovation and enhance our business processes. As part of our
  • commitment to staying ahead in the industry, we are seeking a talented and experienced Data
  • & AI Engineer with strong Azure cloud competencies to join our dynamic team.
  • Job Summary:
  • We are looking for a Senior Machine Learning Engineer with 6+ years of hands-on experience
  • in building, deploying, and optimizing machine learning and AI-driven solutions at scale. This
  • role requires deep expertise in Classical ML, LLM-based applications, real-time machine
  • learning systems, and MLOps frameworks. You will work at the intersection of data science,
  • software engineering, and AI innovation, contributing to cutting-edge AI systems that deliver
  • measurable business value.
  • Key Responsibilities
  • Classical Machine Learning & AI Solutions
  • ¢
  • Design and deploy robust ML models for classification, regression, forecasting, and
  • recommendation engines.
  • Perform advanced feature engineering and data preprocessing on structured and
  • unstructured datasets.
  • Continuously optimize model performance in production environments using scalable
  • tools.
  • LLM Development & Enterprise AI
  • ¢
  • Build and deploy enterprise-grade LLM-based solutions using frameworks like
  • LangChain, LangGraph, CrewAI, and other multi-agent architectures.
  • ¢
  • ¢
  • Implement prompt engineering patterns (e.g., Chain of Thought, ReAct, Tree of
  • Thought) to enhance LLM outputs.
  • Integrate AI workflows with data from enterprise platforms such as SAP and Salesforce.
  • Real-time ML & Full-Stack AI Development
  • ¢
  • Develop real-time machine learning pipelines using Apache Kafka, Flink, or Spark
  • Streaming.
  • ¢
  • ¢
  • Build and maintain end-to-end AI web applications using modern full-stack frameworks.
  • Enable real-time inference and online learning via streaming data pipelines.
  • Databricks ML & MLOps Implementation
  • ¢
  • ¢
  • Leverage Databricks ML (Mosaic AI) and MLflow to manage the ML lifecycle.
  • Implement scalable MLOps pipelines for training, deployment, and monitoring of ML
  • models.
  • ¢
  • Deploy models to production using Azure ML, AWS SageMaker, or Google Vertex AI,
  • ensuring cloud cost optimization and scalability.
  • Multimodal AI & Advanced Retrieval-Augmented Generation (RAG)
  • ¢
  • Design and implement Multimodal AI systems (e.g., text, vision, audio) tailored to
  • business needs.
  • ¢
  • Build advanced RAG and Text2SQL systems, including optimization for edge-case
  • handling and performance tuning.
  • Must-Have Skills
  • ¢
  • ¢
  • 6+ years of experience in ML/AI system development and deployment.
  • Expert in Python and core ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow,
  • PyTorch, Hugging Face). Sound understanding of Statistics, Probability, and ML
  • algorithm fundamentals
  • ¢
  • ¢
  • Proficient in classical ML algorithms, deep learning, and model explainability
  • techniques.
  • Hands-on expertise in MLOps, CI/CD, and model serving tools like vLLM, TensorRT,
  • MLflow, and Docker/Kubernetes.

Skills

DataPythonData BricksBig DataPythonData ScienceDeep LearningImplementationMachine LearningPrompt EngineeringAi EngineerAiMlLlmRagHugging FaceMultimodalLanggraphCrewaiPytorchTensorflowScikit-learnNumpyPandasMlopsMlflowSagemakerVertex AiDatabricksFeature EngineeringData Scientist

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