Data Science Manager/ Sr Manager

6 days ago

Bengaluru Karnataka India, Karnataka Tredence Inc. Full time

Job Description:

  • At least 8 + years of experience in AI/ML, including:
  • A minimum of 2 years leading generative AI applications, focusing on large language models (LLMs), diffusion models, or other advanced AI technologies.
  • 3+ years of experience in NLP-based applications such as ChatBots, Text Classification, Named Entity Recognition (NER), or other NLP-driven projects.
  • Experience with frameworks and tools for building agentic pipelines, such as LangGraph, LLamaIndex, Autogen, PromptFlow, and dspy.
  • Expertise in advanced prompt engineering techniques, including ReACT, Chain of Thought, and Tree of Thought prompting methodologies.
  • Proficiency in evaluating LLM-based applications using frameworks like RAGAS for retrieval-augmented generation and application scoring.
  • Should have strong knowledge on LLM’s foundational model (OpenAI GPT4o, O1, Claude, Gemini etc), while need to have strong knowledge on opensource Model’s like Llama 3.2, Phi etc.


Roles & Responsibilities:

  • Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities:
  • Connect with internal / external POC to understand the business requirements
  • Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis
  • Create project plan and sprints for milestones / deliverables
  • Spin VM, create and optimize clusters for Data Science workflows
  • Create data pipelines to ingest data effectively
  • Assure the quality of data with proactive checks and resolve the gaps
  • Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms
  • Research whether similar solutions have been already developed before building ML models
  • Create optimized data models to query relevant data efficiently
  • Run relevant ML / DL algorithms for business goal seek
  • Optimize and validate these ML / DL models to scale
  • Create light applications, simulators, and scenario builders to help business consume the end outputs
  • Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively
  • Integrate and operationalize the models in client ecosystem
  • Document project artifacts and log failures and exceptions.
  • Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedback

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