Simform

Senior Data Scientist

Simform

full-time

Posted on:

Origin:  • 🇮🇳 India

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Job Level

Senior

Tech Stack

AirflowAWSAzureCloudDockerETLKubernetesPythonPyTorchTensorflow

About the role

  • Lead the design, development, and implementation of enterprise-scale AI/ML solutions optimized for real-world applications
  • Collaborate with cross-functional teams to identify business requirements and translate them into robust AI/ML strategies
  • Develop and optimize generative AI solutions using tools and frameworks such as LangChain, LangSmith, LlamaIndex, MCP, Semantic Kernel, Autogen, and Agents
  • Utilize Python along with frameworks such as PyTorch and TensorFlow to build sophisticated machine learning models and algorithms
  • Conduct analysis of data and identify trends, providing actionable insights to stakeholders
  • Mentor and guide junior data scientists, promoting a culture of innovation and continuous learning
  • Engage with clients to communicate project updates, understand their analytical needs, and deliver tailored AI solutions
  • Apply strong analytical skills to solve complex problems and improve existing models and algorithms
  • Build and manage ETL pipelines, deploy models to production, and monitor models (Docker, Kubernetes, MLflow, Airflow)
  • Build reproducible pipelines for training and serving models

Requirements

  • Minimum 5 years of experience in developing and implementing AI/ML-powered services and algorithms
  • Experience with deep learning models for structured/unstructured data
  • Proven track record of building enterprise-scale AI/ML solutions
  • Extensive hands-on experience with generative AI and large language models (LLMs)
  • Hands-on experience with generative frameworks (LangChain, LangSmith, LlamaIndex, MCP, Semantic Kernel, Autogen, Agents)
  • Proficiency in Python
  • Strong understanding and hands-on experience with ML frameworks such as PyTorch and TensorFlow
  • Familiarity with cloud ML stacks, including Azure and AWS
  • Good understanding of ETL processes and working with data pipelines
  • Model evaluation and validation techniques (cross-validation, hyperparameter tuning)
  • Time Series Analysis and Forecasting
  • Model deployment and monitoring experience (Docker, Kubernetes, MLflow, Airflow)
  • Building reproducible pipelines for training and serving models
  • Strong analytical and problem-solving skills
  • Excellent communication skills and ability to lead cross-functional teams
  • Experience in both team leadership and as an individual contributor
  • Experience engaging with clients and stakeholders to align AI/ML solutions with business objectives