Interesting Job Opportunity: Data Science Lead - Generative AI

Jasper Colin

Website: jaspercolin.com
Job details:
Job Summary

We are seeking a highly skilled Data Science Lead with hands-on experience in Generative AI, Retrieval-Augmented Generation (RAG), and machine learning model development. The ideal candidate will design scalable AI systems, optimize chunking and retrieval strategies, manage vector databases, and fine-tune large language models (LLMs) for enterprise applications.

Key Responsibilities

• Lead the design and deployment of RAG-based GenAI systems using LLMs and embeddings
• Develop and optimize chunking strategies for improved retrieval and context relevance
• Fine-tune transformer-based models (e.g., GPT, LLaMA, Mistral) using LoRA, PEFT, or full-model training
• Implement and manage vector databases (e.g., FAISS, Pinecone, Weaviate) for semantic search
• Build and evaluate machine learning models for classification, regression, clustering, and recommendation systems
• Collaborate with engineering teams to integrate ML and GenAI pipelines into production
• Define and monitor performance metrics for model accuracy, latency, and scalability
• Stay updated with the latest research in GenAI, LLMs, and MLOps
• Mentor junior data scientists and contribute to technical leadership
  
  

Required Skills & Tools

• Programming : Python, SQL
• ML Libraries : scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch
• GenAI Frameworks : Hugging Face Transformers, LangChain, OpenAI API
• Vector Databases : FAISS, Pinecone, Weaviate, Qdrant
• LLM Fine-Tuning : LoRA, PEFT, RLHF, prompt tuning
• Data Engineering : Pandas, NumPy, Spark
• Deployment : FastAPI, Docker, Kubernetes, CI/CD
• Cloud Platforms : AWS, GCP, Azure
• Strong problem-solving and communication :
• Bachelors or Masters degree in Computer Science, Data Science, AI, or related field
• 5 - 7 years of experience in data science, NLP, or machine learning
• Proven track record of building and deploying ML and GenAI applications
  
  

Preferred Attributes

• Experience with open-source LLMs (e.g., Mistral, LLaMA, Falcon)
• Familiarity with semantic search, prompt engineering, and retrieval optimization
• Contributions to AI research or open-source projects
• Certification in Generative AI, NLP, or ML (e.g., DeepLearning.AI, Hugging Face)
  
  

(ref:hirist.tech) Click on Apply to know more.