Associate Staff Engineer, Generative Ai

As a Generative AI Specialist, your role involves leveraging your 5+ years of experience to contribute to cutting-edge projects. You possess a deep understanding of Generative AI fundamentals and transformer-based architectures, as well as expertise in Natural Language Processing (NLP) with models like GPT, BERT, and T5. Your proficiency in Python and key ML libraries such as TensorFlow, PyTorch, and Hugging Face Transformers enables you to work effectively on AI solutions. Key Responsibilities: - Understand clients' business use cases and technical requirements to create elegant technical designs. - Translate decisions and requirements into actionable tasks for developers. - Identify and evaluate different solutions, selecting the best option that aligns with clients' needs. - Define guidelines and benchmarks for non-functional requirements (NFRs) during project implementation. - Write and review design documents that outline the architecture, framework, and high-level design for developers. - Review architecture and design aspects like extensibility, scalability, security, design patterns, user experience, and NFRs, ensuring adherence to best practices. - Develop the overall solution for functional and non-functional requirements, selecting appropriate technologies, patterns, and frameworks. - Apply technology integration scenarios to project requirements and resolve issues raised during code reviews through thorough analysis. - Conduct proof of concepts (POCs) to validate suggested designs and technologies for meeting project requirements. Qualifications Required: - Hands-on experience with prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. - Experience in deploying models on cloud platforms like AWS, GCP, or Azure, with knowledge of MLOps best practices. - Collaboration with product managers, data scientists, and engineering teams to deliver AI-powered solutions. - Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD for ML pipelines. - Strong analytical, problem-solving, and communication skills are essential for this role. (Note: No additional details of the company were provided in the job description.) As a Generative AI Specialist, your role involves leveraging your 5+ years of experience to contribute to cutting-edge projects. You possess a deep understanding of Generative AI fundamentals and transformer-based architectures, as well as expertise in Natural Language Processing (NLP) with models like GPT, BERT, and T5. Your proficiency in Python and key ML libraries such as TensorFlow, PyTorch, and Hugging Face Transformers enables you to work effectively on AI solutions. Key Responsibilities: - Understand clients' business use cases and technical requirements to create elegant technical designs. - Translate decisions and requirements into actionable tasks for developers. - Identify and evaluate different solutions, selecting the best option that aligns with clients' needs. - Define guidelines and benchmarks for non-functional requirements (NFRs) during project implementation. - Write and review design documents that outline the architecture, framework, and high-level design for developers. - Review architecture and design aspects like extensibility, scalability, security, design patterns, user experience, and NFRs, ensuring adherence to best practices. - Develop the overall solution for functional and non-functional requirements, selecting appropriate technologies, patterns, and frameworks. - Apply technology integration scenarios to project requirements and resolve issues raised during code reviews through thorough analysis. - Conduct proof of concepts (POCs) to validate suggested designs and technologies for meeting project requirements. Qualifications Required: - Hands-on experience with prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. - Experience in deploying models on cloud platforms like AWS, GCP, or Azure, with knowledge of MLOps best practices. - Collaboration with product managers, data scientists, and engineering teams to deliver AI-powered solutions. - Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD for ML pipelines. - Strong analytical, problem-solving, and communication skills are essential for this role. (Note: No additional details of the company were provided in the job description.)