Grid Dynamics
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Jobs at Grid Dynamics
Job Description:
Experience: 7 -15 Years
Job Description :
Key responsibilities
As an GEN AI Expert [Min 4 + years of relevant exp on NLP, CV and LLMs], you will be responsible for designing, building, and fine-tuning NLP models and large language model (LLM) agents to solve business challenges. You will play a key role in creating intuitive and efficient model designs that enhance user experiences and business processes. The position demands strong design skills, hands-on coding expertise, advanced proficiency in Python development, specialized knowledge in LLM agent design and development, and exceptional debugging capabilities.
- Model & Agent Design: Conceptualize and design robust NLP solutions and LLM agents tailored to specific business needs, with a focus on user experience, interactivity, latency, failover and functionality.
- Hands-on Coding: Write,test, and maintain clean, efficient, and scalable code for NLP models and AI agents, with a strong emphasis on Python programming.
- Build high quality multi-modal & multi-agents applications/frameworks
- Knowledge on input/output token utilization, prioritization and consumption w.r.t AI agents
- Performance Monitoring: Monitor, optimize LLM agents, implementing model explainability, handling model drift, and ensuring robustness.
- Research Implementation:Ability to read, comprehend, and implement AI Agent research papers into practical solutions. Stay abreast of the latest academic and industry research to apply cutting-edge methodologies and techniques.
- Debugging & Issue Resolution: Proactively identify, diagnose, and resolve issues related to AI agents, including model inaccuracies, performance bottlenecks, and system integration problems. Utilize debugging tools and techniques to troubleshoot complex problems in model behavior, data inconsistencies, and deployment errors.
- Innovation and Research:Stay updated with the latest advancements in AI agents technologies,experimenting with new techniques and tools to enhance agent capabilities and performance.
- Continuous Learning: Adaptability to unlearn outdated practices, patterns, technologies and quickly learn and implement new technologies & papers as the ML world evolves. Maintain a proactive approach to staying current with emerging trends and technologies in Agent based solutions (Text & Multi Modal).
- Clear understanding of tool usage and structured outputs in agents
- Clear understanding of speculative decoding and AST-Code RAG
- Clear understanding of Streaming and Sync/Async processing
- Clear understanding of embedding models and their limitations
Tech stack required:
Programming languages: Python
Public Cloud: Azure
Frameworks: Vector Databases such as Milvus, Qdrant/ ChromaDB, or usage of CosmosDB or MongoDB as Vector stores. Knowledge of AI Orchestration, AI evaluation and Observability Tools. Knowledge of Guardrails strategy for LLM. Knowledge on Arize or any other ML/LLM observability tool.
Experience: Experience in building functional platforms using ML, CV, LLM platforms. Experience in evaluating and monitoring AI platforms in production.
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