Develop and execute AI/ML strategies and projects that deliver business value by automating complex processes, improving efficiency, and enhancing decision-making across the organization.
Drive the automation of repetitive, manual tasks by leveraging AI technologies to reduce time and cost while improving accuracy and operational throughput.
Lead the design and implementation of end-to-end AI and automation solutions, ensuring seamless integration with existing IT infrastructure and business workflows.
Provide thought leadership and oversight in building out the AI function, including Machine Learning Engineers (MLEs) and MLOps capabilities, to automate model deployment, monitoring, and scaling.
Oversee the full AI/ML lifecycle, from model training and optimization to automation of processes for continuous improvement and real-time performance.
Define AI/ML and automation best practices, standards, and governance policies for the organization, ensuring consistent and scalable solutions across departments.
Conduct cutting-edge research on emerging AI technologies, automation tools, and methodologies, and recommend innovative solutions that address specific business challenges in the specialty chemicals and manufacturing sectors.
Monitor and evaluate the performance of AI/ML and automation initiatives, ensuring that systems deliver expected results and continuously improve in alignment with business objectives.
Build, lead, and manage a high-performance team of AI specialists, fostering a culture of innovation, collaboration, and knowledge sharing.
Collaborate closely with business stakeholders to identify and prioritize high-impact AI use cases that align with strategic goals and unlock new automation opportunities.
Communicate the value and progress of AI/ML and automation initiatives to senior leadership, clearly articulating the business impact and potential for future growth.
Stay informed/knowledgeable of industry trends and advancements in AI technology, automation tools, and machine learning models.
Requirements & Skills:
Degree: Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
Years of Related Experience (Min.): 3-5 years of hands-on experience designing and implementing machine learning models as well as AI technologies with a strong focus on automation, preferably within the specialty chemicals or manufacturing industry.
Language: fluent English is essential.
Deep understanding of AI methodologies, automation tools, and technologies, with the ability to apply them effectively to solve complex business problems and drive operational automation.
Up-to-date knowledge of emerging machine learning models, automation frameworks, and relevant AI libraries and tools.
Proven expertise in Generative AI (GenAI) and related technologies, including but not limited to Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Foundation Models (FMs), and Large Language Models (LLMs) such as GPT-4, PaLM 2, DALL·E 2, and LaMDA.
Expertise in cutting-edge automation technologies such as robotic process automation (RPA), AI-driven process mining, and intelligent task automation, with hands-on experience deploying these solutions at scale.
Familiarity with advanced machine learning techniques such as transfer learning, unsupervised feature generation, meta-learning, reinforcement learning, and AI-driven predictive analytics.
Experience with modern data management platforms, cloud environments (e.g., Azure), and scalable data ecosystems that support AI/ML and automation workloads.
Normal expected travel is approximately 10%, possibly higher for key projects.
