Job Description

We are seeking an exceptional AI Architect to lead and drive innovation across our AI initiatives, including Large Language Models (LLMs), Natural Language Processing (NLP), Generative AI (GenAI), Computer Vision (CV), and Machine Learning (ML) for our cutting-edge digital twin product. This role requires a unique blend of technical expertise, leadership skills, and hands-on experience in cloud environments, particularly AWS.

Key Responsibilities

Strategic Leadership:

1. Develop and execute the overall AI strategy for Twyn's digital twin product.
2. Lead and mentor a team of AI specialists, including data scientists, ML engineers, and NLP experts.
3. Collaborate with cross-functional teams to integrate AI solutions into the broader digital twin ecosystem.

Technical Expertise and Innovation:

1. Architect and oversee the development of advanced AI systems, including LLMs, NLP models, GenAI applications, CV algorithms, and ML models.
2. Design and implement multi-physics simulations to enhance the digital twin's predictive capabilities.
3. Stay at the forefront of AI advancements and identify opportunities to apply cutting-edge technologies to Twyn's products.

Cloud Architecture and Implementation:

1. Design and optimize cloud-based AI infrastructure on AWS, ensuring scalability, reliability, and cost-effectiveness.
2. Implement best practices for deploying and managing AI models in cloud environments.
3. Develop strategies for edge computing and distributed AI processing to support real-time digital twin applications.

Data Management and Processing:

1. Oversee the design of data pipelines and architectures to support AI model training and inference.
2. Ensure data quality, security, and compliance across all AI initiatives.
3. Implement efficient data processing techniques for handling large-scale industrial datasets.

AI Model Development and Optimization:

1. Lead the development of custom AI models tailored to digital twin applications in manufacturing and other relevant industries.
2. Optimize model performance, focusing on accuracy, speed, and resource efficiency.
3. Implement techniques for model interpretability and explainable AI to build trust in AI-driven decisions.

Integration and Deployment:

1. Oversee the integration of AI components into the digital twin platform.
2. Develop strategies for continuous deployment and monitoring of AI models in production environments.
3. Ensure seamless interaction between AI systems and other components of the digital twin solution.

Research and Development:

1. Lead R&D efforts to explore emerging AI technologies and their potential applications in digital twin solutions.
2. Collaborate with academic and industry partners to stay at the forefront of AI innovation.

Required Qualifications:

• Ph.D. or Master's degree in Computer Science, AI, Machine Learning, or a related field.
• 10+ years of experience in AI/ML, with at least 5 years in a senior technical leadership role.
• Extensive hands-on experience with LLMs, NLP, GenAI, CV, and ML technologies.
• Strong background in cloud computing, particularly AWS services related to AI/ML.
• Expertise in multi-physics simulations and their integration with AI systems.
• Proficiency in Python and experience with deep learning frameworks (TensorFlow, PyTorch).
• Strong understanding of distributed computing and big data technologies (Spark, Kafka).
• Experience with DevOps practices and MLOps for AI model lifecycle management.
• Proven track record of leading complex AI projects from conception to production.

Preferred Qualifications:

• Experience in the manufacturing industry or with industrial IoT applications.
• Familiarity with digital twin concepts and technologies.
• Publications or patents in AI/ML fields.
• Experience with edge computing and federated learning.

Personal Qualities:

• Exceptional problem-solving and analytical skills.
• Strong leadership and communication abilities.
• Ability to translate complex technical concepts for non-technical stakeholders.
• Passion for innovation and continuous learning.
• Collaborative mindset with the ability to work effectively across teams.