Senior Data Scientist AIML

10 years

40 - 45 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Salary Package: 45 LPA

Work Mode: Hybrid (Kolkata)

Key Responsibilities

  • Design, develop, deploy, and maintain scalable AI/ML models using Python and frameworks like Django/Flask.
  • Build and optimize data pipelines and APIs to integrate machine learning models into production systems.
  • Work across multiple AI domains including NLP, Computer Vision, and Generative AI to deliver impactful solutions.
  • Perform data preprocessing, feature engineering, model training, hyperparameter tuning, and performance evaluation.
  • Collaborate with engineering, product, and business teams to drive AI product development and insights.
  • Implement MLOps best practices for automation, reproducibility, and scalability using Docker, MLflow, Kubernetes, and Azure.
  • Develop and maintain robust CI/CD workflows for ML systems.
  • Document model architectures, experiments, and deployment processes; maintain version control (Git).

Required Qualifications

  • 5–10 years of hands-on experience in AI/ML development and deployment.
  • Strong proficiency in Python and experience with web frameworks (Django/Flask).
  • Deep expertise in Machine Learning, Deep Learning, NLP, and Computer Vision using TensorFlow/PyTorch and scikit-learn.
  • Experience with Generative AI, LangChain, RAG, and LLMs is a strong plus.
  • Strong knowledge of SQL/NoSQL databases, REST API development, and data visualization tools (Power BI/Tableau).
  • Hands-on experience with MLOps/DevOps tools such as Docker, Kubernetes, MLflow, Git, and Azure cloud services.
  • Excellent analytical, problem-solving, and communication skills.
  • Bachelor’s or Master’s degree in Data Science, Computer Science, or a related field (Master’s preferred).

Preferred Skills

  • Experience in building scalable microservices and cloud-native AI solutions.
  • Familiarity with data engineering tools (Apache Spark, Airflow) is a plus.
  • Knowledge of monitoring and logging tools for ML systems.
  • Publications, open-source contributions, or a strong portfolio of AI projects.
Skills: cloud,generative ai,models,data,retrieval-augmented generation (rag),language model’s (llm),data scientist,langchain,nlp,ml,django,computer vision,azure,natural language processing,design

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