【GoingCloud】Senior Data Scientist

Responsibilities

• Lead the design and development of end-to-end data science projects, from business problem understanding to model deployment and monitoring.
• Collaborate with domain experts and cross-functional teams to translate business goals into goal-driven autonomous agent workflows.
• Design and implement robust RAG (Retrieval-Augmented Generation) pipelines to enhance the performance of large language model (LLM) applications.
• Prototype and deploy multi-agent LLM systems for planning, reasoning, and task orchestration.

Build and deploy machine learning models for use cases such as recommendation systems, NLP, time-series forecasting, and computer vision.

Must-Have Skills:

• 5+ years of experience in data science, ML engineering, or applied AI.
• Proficiency in Python and key libraries (NumPy, Pandas, scikit-learn, PyTorch).
• Strong grasp of machine learning algorithms and statistical techniques.
• Familiarity with LLMs and agentic AI techniquesBonus / Preferred Qualifications:
  Prior exposure to recommendation systems, causal inference, or reinforcement learning.

Bonus / Preferred Qualifications:

• Experience building RAG systems (e.g., LangChain, vector search, semantic retrieval).
• Experience with LangGraph, AutoGen, CrewAI or other multi-agent orchestration frameworks.
• Understanding of multi-agent system design patterns (e.g., planner-executor, debate-then-vote, consensus-based reasoning).
• Hands-on experience with AWS AI/ML services (e.g., SageMaker, Bedrock).
• Solid understanding of MLOps best practices, including CI/CD for models.
• Prior exposure to recommendation systems, causal inference, or reinforcement learning.

Our interview process consists of two stages.

• The first round is an interview with the hiring manager and People Team, primarily to understand your relevant past experiences. (Onsite)
• The final stage is your interview with our GM. (Onsite)