VOLT IQ

LLM Fine-Tuning Engineer Location: Hybrid - Bangalore Type: Full-Time About the Role Join our core AI team to develop intelligent systems that transform complex engineering workflows into intuitive conversational experiences. You'll work with cutting-edge language models to create domain-specialized AI solutions for technical applications. Key ResponsibilitiesDomain-Specialized Model Development Adapt large language models to understand technical documentation, specifications, and domain-specific content Optimize model performance for accuracy and reliability in engineering contexts Develop systems for multi-turn contextual reasoning in technical workflows Performance Optimization Implement efficient model deployment strategies for production environments Design hybrid architectures combining retrieval and generation approaches Optimize models for both cloud and edge deployment scenarios Multi-Modal Integration Integrate text, voice, and visual data processing capabilities Enable seamless interaction across different input modalities Develop systems for technical document understanding Innovation & Research Research emerging techniques in model adaptation and optimization Collaborate with domain experts to capture specialized knowledge Stay current with latest developments in LLM fine-tuning methodologies. Technical RequirementsCore Competencies ✅ 1 + years experience fine-tuning large language models using modern frameworks ✅ Expertise in: Parameter-efficient fine-tuning techniques Model optimization for production deployment Evaluation frameworks and custom metrics development ✅ Proficiency in: Python, machine learning operations, and deployment tools Domain Advantage Understanding of engineering workflows and technical documentation Experience with conversational AI systems Knowledge of retrieval-augmented generation approaches Soft Skills 🔍 Strong focus on performance optimization and accuracy trade-offs 💡 Creative approach to data augmentation for specialized domains 🤝 Collaborative mindset for cross-functional team environments QualificationsEducation Computer Science, Engineering, or related technical field Strong foundation in machine learning and natural language processing Portfolio Requirements Demonstrate impact through: Technical projects showcasing model fine-tuning for specialized domains Published research or contributions to AI/ML communities Open-source contributions to relevant projects Experience Production experience with large-scale language model deployments Background with multi-modal AI systems Track record of shipping AI-powered features to end users Bonus Qualifications Contributions to open-source AI/ML projects Experience with voice-enabled applications Background in conversational AI or dialogue systems Prior work in engineering or technical domains