Senior Data Scientist

Overview

About the Role

We are seeking a highly skilled Senior Data Scientist with strong Generative AI (GenAI) expertise to design, develop, and deploy advanced AI/ML solutions. The ideal candidate has deep experience in LLMs, foundation models, MLOps, and end-to-end model development, along with strong problem-solving and leadership capabilities.

Key Responsibilities

• 
  

  Design, fine-tune, and evaluate LLMs, diffusion models, and other generative architectures for domain-specific tasks.

  
  


• 
  

  Build solutions using RAG, prompt engineering, prompt optimization, and agentic workflows.

  
  


• 
  

  Experiment with model distillation, parameter-efficient tuning (LoRA, adapters), and custom pre-training.

  
  


• 
  

  Work with open-source models (Llama, Mistral, Gemma, etc.) and commercial APIs (OpenAI, Azure OpenAI, Anthropic, etc.).

  
  

• 
  

  Build models for prediction, classification, clustering, optimization, time-series, and NLP/NLU.

  
  


• 
  

  Develop and implement feature engineering and model validation frameworks.

  
  


• 
  

  Lead experimentation design, A/B tests, and statistical analysis.

  
  

• 
  

  Deploy scalable ML/GenAI systems using cloud platforms (AWS, Azure, GCP).

  
  


• 
  

  Build and manage model pipelines, monitor model drift, and optimize inference performance.

  
  


• 
  

  Implement CICD workflows using MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML, etc.

  
  

• 
  

  Partner with data engineering teams to design high-quality datasets for training and evaluation.

  
  


• 
  

  Advocate for best practices in data governance, annotation, and quality assurance.

  
  

• 
  

  Translate ambiguous business problems into clear ML problem statements.

  
  


• 
  

  Present insights and recommendations to senior leadership.

  
  


• 
  

  Mentor junior data scientists, guide technical design decisions, and drive innovation across the team.

  
  

Required Qualifications

• 
  

  Master’s or PhD in Computer Science, AI/ML, Data Science, Statistics, or related field.

  
  


• 
  

  5–10+ years of experience in applied ML/Data Science.

  
  


• 
  

  Hands-on expertise with:

  
  
  
  
  • 
    

    Deep learning frameworks: PyTorch, TensorFlow, JAX

    
    
  
  
  • 
    

    LLMs and GenAI toolkits: Hugging Face, LangChain, LlamaIndex

    
    
  
  
  • 
    

    Vector databases: FAISS, Pinecone, Weaviate, Milvus

    
    
  
  
  • 
    

    Cloud ML platforms: Azure ML, AWS SageMaker, Vertex AI

    
    
  
  
  
  


• 
  

  Proficiency in Python, SQL, and production-grade coding.

  
  


• 
  

  Strong understanding of algorithms, optimization, and statistical techniques.

  
  

Preferred Qualifications

• 
  

  Experience building enterprise-grade GenAI applications (chatbots, assistants, knowledge retrieval, code generation, document understanding, etc.).

  
  


• 
  

  Knowledge of RLHF, reward modeling, and safety alignment techniques.

  
  


• 
  

  Exposure to multi-agent systems and orchestration frameworks.

  
  


• 
  

  Publications, patents, or open-source contributions in GenAI/ML.