Senior Data Scientist

nsibilities & deliverables:**

• 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

Required skills & experience:

• 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

Technical Skills:

Aside from Python and SQL, we do not require previous working experience with most of the other skills listed below.

• 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

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