Ask HN: Transitioning from Machine Learning Researcher to Engineer

I recently earned my PhD in applied machine learning with focus on NLP. Although I've started my career with a title of "research engineer," my role leans heavily towards research rather than engineering. I've noticed that most job opportunities where I'm considered a strong candidate tend to be research-oriented. However, I don't envision myself in a long-term career focused on publishing papers; instead, I'm more interested in the ML engineering.

Could anyone share insights or advice on transitioning from a research-focused role to a more engineering-centric position in the field of machine learning? What steps should I take to make myself a more attractive candidate for engineering roles?