AI Implementation Lead

Job Title: Artificial Intelligence (AI) Implementation Lead
About Us
ND Paper is a leading manufacturer of high-quality pulp, paper, and packaging products in the United States, generating over half a billion dollars in annual sales. As a wholly owned subsidiary of Nine Dragons Paper (Holdings) Limited – the largest containerboard producer in the world – ND Paper is part of a global network committed to excellence and innovation. With two integrated pulp and paper mills in Rumford, Maine and Biron, Wisconsin, a packaging plant in Sturtevant, Wisconsin, and two sheeting facilities in Langhorne, Pennsylvania and Fairmont, West Virginia, the ND Paper family produces nearly one million tons of products annually. Our 1,100 dedicated employees are the heart of our operations, and we are committed to fostering positive work environments where individuals can advance and thrive. At ND Paper, we are investing in our future, and that starts with our staff. This position will be located in Toronto, Canada.

Position Overview
We are seeking a highly motivated and skilled AI Implementation Lead to champion the adoption and integration of AI technologies across our manufacturing operations. This is a critical, hands-on role that bridges the gap between business needs and technical solutions. You will be responsible for the entire AI project lifecycle, from identifying use cases and developing prototypes to deploying and maintaining scalable AI systems, all while working closely with our existing IT team and operations staff.

Job Responsibilities

• Demonstrate safety as a core value and establish a safe work environment by actively leading the safe execution of work.
• Strategy & Planning: Identify opportunities for AI to improve efficiency, quality, and decision-making in manufacturing processes (e.g., predictive maintenance, quality control, demand forecasting, logistics planning).
• End-to-End Implementation: Lead AI projects from requirements gathering and solution design through development, testing, deployment, and ongoing support, working within the constraints of a small IT team.
• Technical Development: Design, develop, and deploy AI/ML models and algorithms using programming languages like Python and relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Data Management & Engineering: Collaborate with the IT team to build and maintain robust data pipelines for data ingestion, processing, and storage, ensuring high data quality for AI models.
• System Integration: Ensure seamless integration of AI solutions with existing systems and infrastructure (e.g., IoT sensors, ERP systems, manufacturing execution systems), leveraging cloud platforms where appropriate.
• Collaboration & Change Management: Work closely with cross-functional teams, including operations, engineering, and the IT department, to align AI initiatives with business objectives and facilitate smooth user adoption through effective training and communication.
• Performance Monitoring & Optimization: Monitor the performance, reliability, and security of deployed AI applications, making continuous improvements based on data analysis and feedback.
• Ethics & Compliance: Ensure all AI initiatives adhere to data privacy, security, and ethical standards.

Attributes for Success

• Hard work – tackle each task with determination, passion and creativity; the willingness to put in whatever effort is required to successfully complete the job at hand.
• Pursuit of Excellence – strive to consistently exceed expectations in our day-to-day work and outperform our competitors in the marketplace, regarding work and company achievements as a collaborative goal with the desire to go above and beyond.
• Integrity - treat the company and teammates with upmost respect, operating on strong moral codes to drive company values and culture.
• Sense of Urgency – drive forward each day with speed, agility, and flexibility to capture unrealized opportunities and avoid potential risks for the business.
• Entrepreneurial Spirit – act like an owner, challenging the status quo, asking the right questions, and actively seeking ways to innovate and improve.
• Adaptability – be fluid with ND Paper's continuous evolution while driving change in a fast-paced environment, equipped with the ability to acclimate quickly.
• Servant Leadership – set an example by implementing meaningful leadership with heart, empathy, foresight and stewardship.

Required Experience

• Education: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field OR the equivalent training and/or experience.

• Experience:

• 2-5 years proven experience in successfully implementing AI/ML projects in a real-world business setting, preferably within a manufacturing or industrial environment.

• Hands-on experience with the full AI development lifecycle and MLOps practices.

• Experience collaborating with or leading projects within lean IT environments, demonstrating resourcefulness and practical problem-solving.

• Technical Skills:

• Strong proficiency in Python and relevant AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).

• Familiarity with cloud platforms (AWS, Azure, or GCP) and data engineering tools/practices.

• Knowledge of database systems and data modeling techniques.

• Soft Skills:

• Strong communication and stakeholder management abilities to translate complex technical concepts to non-technical audiences.

• Critical thinking and problem-solving skills to identify challenges and devise innovative solutions.
• Adaptability and leadership to navigate the changes and uncertainties inherent in AI adoption within an established industry.
• Business acumen to align AI solutions with tangible business value and ROI.

Preferred Qualifications

• Domain knowledge of manufacturing processes, such as quality control, supply chain optimization, and predictive maintenance.
• Experience with containerization and orchestration tools like Docker and Kubernetes.
• Proven track record of delivering measurable impact and business value through AI solutions.
• Proficiency in Mandarin, spoken and written, preferred.

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