post job vacancy
Location: San Jose, CA (Onsite)
Contract
Job Summary:
We are seeking an experienced and visionary Generative AI Architect to lead the design, development, and deployment of cutting-edge AI solutions using generative technologies (e.g., LLMs, diffusion models). You will be at the forefront of innovation, shaping scalable AI architectures, collaborating with cross-functional teams, and driving the successful adoption of GenAI across the organization.
Key Responsibilities:
Design scalable, secure, and high-performance architectures for generative AI applications.
Lead the end-to-end lifecycle of GenAI initiatives – from problem discovery, data strategy, model selection, fine-tuning, to deployment and monitoring.
Evaluate and integrate LLMs (e.g., GPT, Claude, LLaMA), image/video generation models (e.g., Stable Diffusion, DALL·E), and other GenAI systems.
Collaborate with data scientists, MLOps engineers, product managers, and domain experts to define and deliver impactful AI solutions.
Select appropriate cloud platforms (AWS, Azure, GCP) and MLOps pipelines to support AI workloads.
Ensure compliance with security, privacy, and ethical guidelines around AI development and deployment.
Stay updated with the latest trends, research, and advancements in generative AI and apply them to real-world use cases.
Guide technical teams and provide mentorship to junior AI engineers and researchers.
Required Qualifications:
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
7+ years of experience in AI/ML with at least 2–3 years focused on generative models.
Strong hands-on experience with transformer architectures, LLMs, and/or generative media models.
Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers, LangChain, etc.).
Deep understanding of MLOps best practices, model lifecycle management, and cloud-native architecture.
Experience with prompt engineering, fine-tuning, and RAG (Retrieval-Augmented Generation) workflows.
Preferred Qualifications:
Experience deploying GenAI models in production environments.
Knowledge of vector databases (e.g., FAISS, Pinecone) and semantic search.
Familiarity with open-source LLMs and open-weight models (e.g., Mistral, LLaMA2, Falcon).
Contributions to research, open-source projects, or patents in the GenAI space.
Strong communication and stakeholder management skills.
To apply for this job email your details to sumit.s@amaze-systems.com