We are seeking a highly skilled and visionary Senior AI/ML Architect with deep expertise in Generative AI, AWS Textract, Computer Vision, and Natural Language Processing (NLP). The ideal candidate will lead the design and architecture of AI/ML-powered solutions that solve complex business challenges, focusing on document automation, large-scale data extraction, and intelligent systems integration. You will be responsible for shaping the end-to-end architecture of AI systems while ensuring scalability, security, and robustness of deployed solutions.
Key Responsibilities:
AI/ML Architecture Leadership: Lead the design, architecture, and deployment of large-scale AI/ML solutions, focusing on integrating Generative AI, NLP, AWS Textract, and Computer Vision technologies into production environments.
End-to-End Solution Design: Architect comprehensive AI/ML pipelines that encompass data ingestion, preprocessing, model training, inference, and deployment, leveraging cloud infrastructure (AWS) for scalability and high performance.
Generative AI & NLP Strategy: Design NLP models and Generative AI systems that can process, understand, and generate human-like text, enabling solutions like automated document analysis, summarization, and generation.
AWS Textract & Document Automation: Architect solutions using AWS Textract and related AWS AI services for automated document extraction, classification, and data extraction tasks.
Computer Vision Integration: Lead the development of computer vision solutions to extract and analyze information from images, scanned documents, PDFs, and other formats. Architect the integration of vision models into larger AI pipelines.
Cloud Infrastructure: Design robust and scalable cloud-based AI solutions using AWS services, including SageMaker, Lambda, EC2, and S3. Ensure seamless integration with cloud infrastructure for reliable model deployment and orchestration.
AI Security & Governance: Develop secure AI models and architectures, ensuring data privacy and compliance with regulatory standards. Implement model monitoring, governance, and lifecycle management.
Collaboration & Stakeholder Engagement: Collaborate with product teams, business stakeholders, and data scientists to align AI/ML solutions with business goals. Communicate complex technical concepts and project progress to non-technical stakeholders.
Research & Innovation: Stay at the forefront of AI/ML research, exploring the latest trends in Generative AI, computer vision, and NLP. Identify opportunities to incorporate state-of-the-art techniques into the architecture to enhance solution capabilities.
MLOps and Automation: Lead the adoption of MLOps practices, automating the model development lifecycle from development to production, including monitoring, versioning, and continuous integration/continuous deployment (CI/CD).
Qualifications:
Education: Bachelor's or master's degree in computer science, AI/ML, Data Science, or related fields. PhD is a plus.
Experience:
10+ years of experience in designing, architecting, and deploying large-scale AI/ML systems with a focus on Generative AI, Computer Vision, NLP, and AWS cloud infrastructure.
Proven experience in deploying AI solutions using AWS services such as AWS Textract, Comprehend, SageMaker, and Lambda.
Expertise in designing architectures for NLP models, transformer-based models (BERT, GPT, etc.), and large language models.
Deep understanding of computer vision techniques (CNNs, YOLO, OCR) and integration with cloud-based systems.
Hands-on experience with MLOps frameworks and practices.
Skills:
Proficiency in AI/ML frameworks (TensorFlow, PyTorch) and cloud platforms (AWS).
Expertise in NLP tools like Hugging Face, SpaCy, and NLP Transformers.
Strong experience in AWS AI services (Textract, Comprehend, Lambda) for document automation and data extraction workflows.
Expertise in designing scalable AI architectures for cloud-based environments.
Excellent knowledge of containerization (Docker) and orchestration in deploying AI solutions.
Strong problem-solving abilities and experience in optimizing AI/ML models for production.
Soft Skills: Strong communication skills to effectively explain AI/ML architectures to non-technical stakeholders, with leadership experience in driving cross-functional AI projects.
Preferred Qualifications:
Experience designing and deploying AI-powered document processing solutions specifically for the Financial Services sector is highly desirable.
Expertise in building multi-modal AI systems that integrate vision, NLP, and structured data.
Familiarity with security best practices for AI models, particularly in regulated industries.
Experience with agile development processes and distributed teams.