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.
