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 energetic 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

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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

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Build and deploy enterprise-grade LLM-based solutions using frameworks like

LangChain, LangGraph, CrewAI, and other multi-agent architectures.

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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

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Develop real-time machine learning pipelines using Apache Kafka, Flink, or Spark

Streaming.

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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

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Leverage Databricks ML (Mosaic AI) and MLflow to manage the ML lifecycle.

Implement scalable MLOps pipelines for training, deployment, and monitoring of ML models.

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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)

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Design and implement Multimodal AI systems (e.g., text, vision, audio) tailored to business needs.

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Build advanced RAG and Text2SQL systems, including optimization for edge-case handling and performance tuning.

Must-Have Skills

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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

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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.

📌 Data Scientist - BLR (Bengaluru)
🏢 Celebal Technologies
📍 Bengaluru