Game Tester Freshers Walk-in Drive - GlobalStep Pune

Salary

Not Disclosed

Location

Hyderabad

Highlights

Designing agent-based architectures, fine-tuning LLMs, developing NLP solutions, optimizing models, and collaborating on cross-functional teams.

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Description

We are seeking a proficient AI Engineer with a robust background in Agentic Artificial Intelligence and Natural Language Processing (NLP). This role requires the candidate to design, develop, and deploy intelligent systems using advanced Large Language Models (LLMs), multi-agent frameworks, and autonomous agents. The ideal candidate will have hands-on experience with cutting-edge tools such as CrewAI, LangGraph, AutoGen, LangChain, and similar platforms.

• Design agent-based architectures for real-world problem-solving
• Build multi-agent workflows for task orchestration, decision-making, and execution
• Integrate LLMs with various tools, APIs, and memory systems to enhance model performance
• Fine-tune pre-trained models like Mistral Large, Gemini Flash, and OpenAI models for specific applications
• Create NLP solutions for summarization, classification, and text generation
• Contribute to internal or open-source model repositories by developing new modules and features
• Pre-process and analyze large-scale datasets using advanced data engineering techniques
• Collaborate with cross-functional teams on scalable data pipelines and evaluation metrics
• Optimize models for performance, latency, and scalability in production environments
• Stay current with the latest advancements in LLMs, agentic architectures, and AI safety practices
• Maintain comprehensive technical documentation for models and agent workflows
• Present findings to both technical and non-technical stakeholders at various levels of the organization

The role demands a combination of strong problem-solving skills, deep technical expertise in programming languages like Python, and experience with frameworks such as PyTorch or TensorFlow. A solid understanding of distributed systems, large-scale data processing, and AI safety is crucial for success.

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Skills

Python-programming PyTorch-/-TensorFlow LLMs-and-prompt-engineering WatsonX,-LangChain,-AutoGen Distributed-systems Large-scale-data-processing NLP-solutions-development Model-evaluation-&-optimization Cross-functional-collaboration AI-safety-practices