qode.world
Data Scientist
🇺🇸 New Jersey, NJ
🕑 Full-Time
💰 TBD
💻 Data Science
🗓️ August 27th, 2025
Langchain
LLAMA
Pandas
Edtech.com's Summary
Qode is hiring a Data Scientist to develop and deploy advanced machine learning and deep learning models, including classification, regression, and forecasting. The role involves designing NLP pipelines, fine-tuning large language models, building multi-agent AI systems, and collaborating with cross-functional teams to deliver production-ready solutions while mentoring junior data scientists.
Highlights
- Build and optimize classification, regression, and forecasting models using classical ML and deep learning techniques.
- Develop deep learning architectures such as LSTMs, transformers for time-series, NLP, and anomaly detection.
- Design NLP pipelines for text classification, semantic search, summarization, and question answering using transformer-based models.
- Create retrieval-augmented generation (RAG) pipelines integrating LLMs with vector databases like FAISS and Pinecone.
- Fine-tune LLMs (OpenAI, Mistral, LLaMA, Cohere) with supervised methods or LoRA/QLoRA for domain-specific tasks.
- Build multi-agent AI systems using frameworks like LangGraph and CrewAI for autonomous decision-making workflows.
- Collaborate with data engineers, product managers, and stakeholders to translate business needs into production solutions.
- Mentor junior data scientists through code reviews and model design feedback.
- Proficient in Python and libraries/frameworks: scikit-learn, pandas, PyTorch, TensorFlow, Hugging Face Transformers, LangChain.
- Requires 5+ years of data science or applied machine learning experience and a Bachelor's degree.
Data Scientist Full Description
Data Scientist -
Key Responsibilities
- Build and optimize classification, regression, and forecasting models using classical ML and deep learning techniques.
- Develop and deploy deep learning architectures including LSTMs, transformers, and other sequence-based models for time-series, NLP, and anomaly detection.
- Design and implement NLP pipelines for text classification, semantic search, summarization, and question answering using transformer-based models (e.g., BERT, T5, GPT).
- Create RAG (retrieval-augmented generation) pipelines integrating LLMs with vector databases (e.g., FAISS, Pinecone, Weaviate) and document indexing frameworks.
- Apply and fine-tune LLMs (e.g., OpenAI, Mistral, LLaMA, Cohere) for domain-specific tasks using supervised fine-tuning or LoRA/QLoRA methods.
- Build and orchestrate multi-agent AI systems using frameworks like LangGraph, CrewAI, or OpenAgents to support tool-using, autonomous agents for decision-making workflows.
- Collaborate with data engineers, product managers, and stakeholders to translate business needs into production-ready solutions.
- Mentor and support junior data scientists through code reviews, model design feedback, and collaborative experimentation.
- Promote best practices in reproducible modeling, responsible AI, and scalable deployment.
Required Skills & Experience
- 5+ years of experience in data science or applied machine learning, with a strong background in both classical and deep learning methods.
- Hands-on experience with Python, and libraries/frameworks such as scikit-learn, pandas, PyTorch, TensorFlow, Hugging Face Transformers, and LangChain.
- Strong understanding of classification metrics, feature engineering, model validation, and hyperparameter tuning.
- Demonstrated experience with LLMs, including fine-tuning, prompt engineering, and retrieval-augmented generation techniques.
