<p>Aging societies have created a need to accelerate knowledge transfer between workers, and rapidly improve the skills of novice workers. This paper proposes a scheduling – based strategy that accounts for skill improvement in a mechanical engineering design activity of an Engineer-to-Order (ETO) production system. A metaheuristic-based solution is proposed, using a tabu-search based algorithm. A posteriori Pareto optimization is used to derive non-dominated solutions for each iteration. Furthermore, a hybrid neighbourhood structure is proposed, with neighbourhoods designed to address the objective functions. A paired assignment method, based on the Cognitive Load Theory (CLT) is suggested as a method to implement rapid skill development. The proposed algorithm is validated against the results of an exact brute force method, and the proposed hybrid neighbourhood is evaluated against existing neighbourhood structures proposed in literature. To evaluate the effectiveness of the proposed scheduling method under various jobs, engineers, and workload conditions, multiple tests are conducted over a span of 6 months. The results are compared with those simulated for the current scheduling practices in ETO design engineering activities. The findings indicate that over the long term, the proposed method leads to better skill improvement in all scenarios. Additionally, it outperforms existing practice in terms of total tardiness under most conditions, except in situations with the highest workload settings or workplaces with a higher proportion of expert-level engineers.</p>