Generative AI Engineer

Our associate is seeking a Senior AI Engineer specializing in generative AI models, with a focus on image generation and conversational AI systems. The ideal candidate will have deep expertise in training, fine-tuning, and deploying large language models (LLMs) and image generation models, combined with strong backend development skills for production deployment.

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• Develop and fine-tune image generation models (Stable Diffusion, DALL-E style architectures)

• Build and optimize large language models for conversational AI applications

• Design and implement training pipelines for generative AI models

• Create efficient prompt engineering systems and frameworks

• Develop model evaluation and quality assessment frameworks

• Implement RLHF (Reinforcement Learning from Human Feedback) pipelines

• Build and maintain model serving infrastructure for real-time inference

• Design data collection and curation pipelines for model training

• Optimize model performance and reduce inference costs

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• 4+ years of experience in deep learning and generative AI

• Strong expertise in image generation models (Diffusion models, GANs)

• Experience with LLMs and transformer architectures

• Proficiency in fine-tuning and training generative models

• Deep understanding of prompt engineering and optimization

• Experience with model quantization and optimization techniques

• Strong Python programming skills

• Experience with distributed training systemsTechnical Requirements

Core Technologies:

• Runtime: Node.js

• Frameworks: Express.js, NestJS

• Databases:

▪ MongoDB

▪ PostgreSQL

▪ Redis for caching

• API Development:

▪ RESTful APIs

▪ GraphQL

▪ WebSocket

▪ API Documentation (Swagger/OpenAPI)

Additional Tools & Technologies:

• Version Control: Git

• Testing: Jest, Mocha, Supertest

• Queue Systems: RabbitMQ, Redis Queue

• Containerization: Docker, Kubernetes

• CI/CD: Jenkins, GitHub Actions

• Monitoring: New Relic, Datadog, ELK Stack

• Image Generation Frameworks:

​•​Stable Diffusion

​•​DALL-E

​•​ControlNet

​•​Custom diffusion models

• Language Models:

​•​GPT architecture

​•​LLaMA

​•​Mistral

​•​BERT/RoBERTa

• Deep Learning Frameworks:

​•​PyTorch

​•​Hugging Face Transformers

​•​JAX/Flax

• Training Tools:

​•​DeepSpeed

​•​PEFT (Parameter Efficient Fine-Tuning)

​•​LoRA/QLoRA

​•​Accelerate

Key Competencies:

• Expertise in generative AI architectures and training methods

• Strong understanding of prompt engineering techniques

• Experience with model distillation and compression

• Knowledge of RLHF and model alignment

• Understanding of training data requirements and curation

• Experience with model evaluation metrics

• Ability to optimize inference performance and costs

What Sets You Apart:

• Experience with real-time data processing.

• Experience building custom training architectures

• Knowledge of advanced prompt engineering techniques

• Expertise in model alignment and safety

• Experience with multi-modal models

• Understanding of AI ethics and bias mitigation

• Contributions to generative AI open-source projects

• Research publications in generative AI

• Knowledge of messaging systems and event-driven architectures.

• Familiarity with serverless architectures.

• Experience with system monitoring and logging.

• Understanding of DevOps practices.

• Contributions to open-source projects.

• Experience with API gateway implementation.

Problem-Solving Abilities:

• Strong analytical and debugging skills.

• Ability to optimize system performance.

• Experience in troubleshooting production issues.

• Capacity to implement elegant solutions for complex problems.

• Skill in identifying and resolving security vulnerabilities.

System Improvement Focus

• Experience in legacy system modernization.

• Ability to identify and implement system improvements.

• Knowledge of performance monitoring and optimization.

• Experience with automated testing and quality assurance.

• Understanding of scalability patterns and practices.

Professional Qualities:

• Strong communication skills.

• Proactive problem-solving approach.

• Ability to work independently and in teams.

• Excellence in technical documentation.

• Mentoring capabilities for junior developers.

• Commitment to code quality and best practices.

Additional Responsibilities:

• Lead research initiatives in generative AI

• Conduct model architecture reviews

• Mentor team members in AI development

• Establish best practices for model development

• Participate in AI safety discussions

• Collaborate with product teams on AI features

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• Competitive salary package.

• Remote work options.

• Health and wellness benefits.

• Professional development budget.

• Regular training opportunities.

• Performance bonuses.

• Modern work equipment.

Work Environment

• Collaborative team structure.

• Agile development methodology.

• Focus on continuous improvement.

• Regular knowledge sharing sessions.

• Emphasis on work-life balance.

• Opportunities for career growth.

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