Senior Data Scientist

Responsibilities

What will you contribute?

We are seeking an experienced Senior Data Scientist to join our AI innovation team, with a specialty in developing and deploying production-grade Large Language Model (LLM) systems. The ideal candidate will be at the forefront of artificial intelligence technology, with deep experience across the full lifecycle of LLM applications - from research and development to production deployment and monitoring.

In this role, you will collaborate with cross-functional teams to design, implement, and optimize LLM-based solutions that drive business value across our internal functions and client-facing products. You will be responsible for building robust, scalable AI systems that can perform a wide variety of natural language tasks while maintaining high standards of reliability, efficiency, and ethical AI practices.

• Design, develop, and deploy production-grade large language model systems across a wide variety of applications (e.g. RAG, text-to-SQL, specialized agents etc., summarization, etc.)
• Architect and implement agent and multi-agent systems leveraging state-of-the-art LLM frameworks
• Creation of tools and functions to enhance LLM capability
• Establish and maintain model lifecycle management practices, including version control, evaluation metrics, and performance monitoring
• Optimize LLM applications for production environments, balancing performance, cost, and latency requirements
• Perform robust model validation and security assessments of LLM systems
• Collaborate closely with product teams, data engineers, and software engineers to integrate LLM capabilities into products and services
• Lead technical discussions and present complex AI concepts to both technical and non-technical stakeholders
• Stay current with the rapidly evolving LLM landscape and implement best practices
• Mentor junior data scientists and engineers across the organization in LLM development techniques

• 5+ years of professional experience in data science or machine learning engineering
• Proven experience developing and deploying production-grade large language model systems
• Strong proficiency in Python and related data science/ML libraries
• Experience with LLM frameworks such as LangGraph or similar orchestration tools
• Practical knowledge of prompt engineering, fine-tuning, retrieval-augmented generation, text-to-sql, and other related LLM tasks
• Experience implementing agent and multi-agent systems with LLMs
• Strong knowledge of deploying LLM systems and agents in production environments
• Strong understanding of model lifecycle management and monitoring practices
• Familiarity with cloud environments (e.g. Azure, databricks) and MLOps best practices
• Experience with distributed computing and handling large-scale data processing
• Thorough understanding of security best practices around LLM systems
• Excellent collaboration skills and experience working with cross-functional teams
• Strong knowledge of software development best practices (version control, CI/CD, testing)
• Exceptional leadership, communication, and presentation skills
• Advanced degree (MS or PhD) in Computer Science, Machine Learning, or related technical field

• Programming Languages: Python (required), SQL
• ML/LLM Frameworks: LangChain, LangGraph, Hugging Face Transformers, PyTorch, TensorFlow, or equivalent
• Vector Databases: Pinecone, Weaviate, Milvus, Qdrant, or similar
• Cloud Platforms: Azure, Databricks, AWS, or equivalent
• MLOps Tools: MLflow, Weights & Biases, Kubeflow, or similar
• Development Tools: Git, GitHub/GitLab, CI/CD pipelines
• Data Processing: Pandas, PySpark, Dask, Spark, or equivalent
• Containerization: Docker, Kubernetes
• API Development: FastAPI, Flask, Langgraph Platform
• Monitoring & Observability: Langsmith, Prometheus, Grafana, or similar