LLM Fine-Tuning Engineer

LLM Fine-Tuning Engineer

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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

+ years experience

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