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AI System Architect
2 weeks ago
We are seeking a visionary leader to spearhead the development of large-scale AI solutions. This role requires an individual who can bridge the gap between business objectives and technical implementation, leveraging deep expertise in generative AI and modern MLOps practices.
Key Responsibilities
AI Solution Design & Implementation
Architect end-to-end AI systems leveraging large language models and generative AI technologies
Design scalable, production-ready AI applications that meet business objectives and performance requirements
Evaluate and integrate LLM APIs from leading providers
Establish best practices for prompt engineering, model selection, and AI system optimization
Model Development & Fine-tuning
Fine-tune open-source models for specific business use cases
Implement custom training pipelines and evaluation frameworks
Optimize model performance, latency, and cost for production environments
Stay current with latest model architectures and fine-tuning techniques
Infrastructure & Deployment
Deploy and manage AI models at enterprise scale using containerization and orchestration
Build robust, scalable APIs using FastAPI and similar frameworks
Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment
Ensure high availability, security, and performance of AI systems in production
Business & Technical Leadership
Collaborate with stakeholders to understand business problems and translate them into technical requirements
Provide technical guidance and mentorship to development teams
Conduct feasibility assessments and technical due diligence for AI initiatives
Create technical documentation, architectural diagrams, and implementation roadmaps
Required Qualifications
Experience
7+ years of experience in machine learning engineering or data science
Proven track record of delivering large-scale ML solutions
Technical Skills
Expert-level proficiency with LLM APIs
Hands-on experience fine-tuning transformer models
Strong proficiency in FastAPI, Docker, and Kubernetes
Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers)
Proficiency in Python and modern software development practices
Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services
Core Competencies
Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques
Experience with MLOps tools and practices (model versioning, monitoring, CI/CD)
Ability to translate complex business requirements into technical solutions
Strong problem-solving skills and architectural thinking
Preferred Qualifications
Experience with vector databases and retrieval-augmented generation (RAG) systems
Knowledge of distributed training and model parallelization techniques
Experience with model quantization and optimization for edge deployment
Familiarity with AI safety, alignment, and responsible AI practices
Experience in specific domains (finance, healthcare, legal, etc.)
Advanced degree in Computer Science, AI/ML, or related field
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