AI System Designer

1 week ago

Gurgaon Gurugram Bengaluru Bangalore Noida, India beBeeArtificialIntelligence Full time US$ 1,20,000 - US$ 2,00,000
Job Description

Develop AI Solutions for Business Growth:

  • Design and Develop AI Models: Create cutting-edge generative models using techniques such as GPT, GANs, VAEs, and diffusion models to tackle tasks like text generation, summarization, reasoning, Q&A, and predictive analytics.
  • Fine-Tune Pre-Trained Models: Refine pre-trained models (e.g., Llama3, Mistral, OpenAI GPT, BERT, T5) to meet specific business requirements.
  • Data Preparation: Clean, preprocess, and structure large datasets to train, validate, and test generative AI models.
  • Deployment: Implement scalable solutions for deploying generative AI models in production environments using tools like Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure).
  • Collaboration: Work closely with cross-functional teams, including product managers, engineers, and stakeholders, to align AI solutions with business goals.
  • Evaluation: Develop metrics and benchmarks to evaluate model performance and ensure quality outputs.
  • Research: Stay up-to-date with the latest advancements in AI/ML, particularly in generative AI techniques, and propose innovative solutions.
  • Responsible AI Practices: Ensure ethical considerations are addressed in model development, including fairness, accountability, and explainability. Experience in architecting AI systems to solve complex business problems.
  • LLM Development and Orchestration: Build advanced RAG pipelines, text chunking, and retrieval, LLM prompt engineering, using Vector Databases. Implement the right LLM selection based on use cases and client criteria (GPT-4, Llama2, Mistral, Claude, Gemini, Flan, BERT) while managing the trifecta of accuracy, cost, and latency/scale.
  • State-of-the-Art NLP Model Development: Develop, fine-tune, context tune, and implement state-of-the-art NLP models including Large Language Models like GPT, Llama3.1, Claude, BLOOM, Flan-T5, Falcon etc. Fine-tuning PEFT LoRa/QLoRa adapters.
  • AI Systems and Architectures: Design AI systems & architectures, while considering good Responsible AI standards and AI Governance.
  • Agentic AI and Autonomous Agents: Build Agentic AI, AutoGen, Multi-agents use cases, AI Autonomous Agents and LLM orchestration architectures for enterprise data at scale in Python.
  • Complementary Technologies: Hands-on experience with complementary technologies around LLMs like embedders, vector databases (chroma, weaviate etc.), orchestration tools like Langchain, LlamaIndex etc.
  • Research and Experimentation: Conduct research and experimentation to improve existing models and propose novel approaches.
  • Integration and Collaboration: Collaborate with cross-functional teams to integrate generative AI solutions into real-world applications.
  • Knowledge Sharing: Stay up-to-date with the latest advancements in deep learning and generative models and apply them to enhance our AI capabilities.
  • Documentation and Communication: Document research findings, prepare technical reports, and contribute to whitepaper/scientific publications.
  • Leadership and Coaching: Provide deep leadership and coaching in the project delivery lifecycle. Focus on shared learning, continuous improvement, and drive adoption of best practices.

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