Senior Data Scientist - Generative AI
5 to 10 years overall work experience, with at least 1 year in Generative AI
Essential functions
Design and implement end-to-end generative AI solutions including RAG chatbots, LLM-powered BI systems, and coding agents
Develop and deploy AI agents using frameworks like LangGraph and similar orchestration tools
Build robust data processing pipelines using LlamaIndex and related libraries for document ingestion and retrieval
Implement and optimize vector databases for semantic search and retrieval systems
Integrate multiple LLM providers (OpenAI, Gemini, Anthropic) and evaluate model performance
Set up comprehensive observability and monitoring using tools like LangSmith
Collaborate with engineering teams to productionize ML models and AI applications
Qualifications
Required Skills:
Generative AI (Minimum Requirements):
Hands-on experience with LangGraph or similar AI agent frameworks
Proficiency with LlamaIndex, LangChain, or equivalent data processing libraries
Experience with vector databases (Pinecone, Weaviate, Chroma, etc.)
Working knowledge of multiple LLMs and their APIs (OpenAI GPT, Gemini, Claude)
Experience with LLM observability tools (LangSmith, Weights & Biases, etc.)
Proven track record in building LLM BI solutions (natural language to SQL)
Experience developing RAG (Retrieval-Augmented Generation) chatbots
Experience with coding agents and code generation systems
Traditional AI/ML:
Strong foundation in clustering, regression, classification, and forecasting
Proficiency with scikit-learn, PyTorch, TensorFlow
Experience with statistical analysis and experimental design
Knowledge of feature engineering and data preprocessing techniques
Would be a plus
Good to Have:
Fine-tuning experience with LLMs, rerankers, or embedding models
Self-hosting and deployment of open-source LLMs
Experience with BERT, transformer architectures, or computer vision models (YOLO)
MLOps experience with MLflow, Weights & Biases, or TensorBoard
Cloud platform certifications (AWS, GCP, Azure)
Additional Requirements:
Strong programming skills in Python
Experience with containerization (Docker, Kubernetes)
Knowledge of API development and microservices architecture
Understanding of prompt engineering and prompt optimization techniques
Experience with evaluation frameworks for LLM applications
Familiarity with data privacy and security best practices for AI applications
We offer
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.Apply to the position
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