What do you do if you're a mid-career professional in machine learning struggling with imposter syndrome?

Recognize it and improve. If you have a colleague who seems to you to be more knowledgeable, then discuss this topic with him. Find out his resources to learn what you don't know. And repeat what you already know and MORE PRACTICE.

Even people who are considered experts often suffer from imposter syndrome. I've experienced it myself, especially when I am surrounded by much younger colleagues who seem to be more expert in the latest ML methods than I am. Being aware of the problem helps. Then remember that we all have our strengths and weaknesses. and that not knowing everything doesn't mean you don't know anything. Acknowledge your weaknesses, but also know and celebrate your strengths. That won't eliminate imposter syndrome, but it should mitigate it a bit.

You can ask for support from both colleagues and those closest to you. Some of them will advise you on how to improve your missing knowledge, some will try to convince you that you are, after all, a professional in your field and hold a specific position for a reason.

As a mid-career professional grappling with imposter syndrome in machine learning, setting clear and achievable goals can be a game-changer. Start by defining specific objectives that align with your career aspirations and skill development needs. Break down larger goals into smaller, actionable steps, and celebrate each milestone along the way. Cultivate a growth mindset and seek out opportunities for learning and mentorship to build confidence in your abilities. Remember that it's okay to ask for help and that setbacks are a natural part of the learning process. By setting goals and nurturing self-belief, you can overcome imposter syndrome and thrive in your ML journey.

Continue to learn new things, repeat what you have already learned, and practice new and old things. This will help you convince yourself that you are here for a reason, that you have the necessary knowledge in a particular area and are still capable of learning new things. And practice will help with this and will bring your actions in certain situations to automaticity.

Instead of thinking that you don’t know or can’t do something, think about what you KNOW and what you CAN. You have been working in this field for some time, you have already solved some problems, you may have even already received a promotion. All this was for a reason, but because you are doing your job. As for what you don’t know, just study what interests you and develop in these areas. Soon you will be a professional at them too.

Sharing your knowledge and experience, regardless of your expertise level, can impact others in the machine learning community. You possess insights, skills and experience that can benefit individuals who are embarking on their journey in this field. Remember, mastery isn't measured solely by years of experience but by the depth of understanding and ability to impart that knowledge. By mentoring others, you not only reinforce your own understanding but also gain fresh insights into your strengths and areas for growth. Embrace the opportunity to guide and support newcomers, as it not only enriches their learning but also reaffirms your place as a valued member of the ML community.