I confirm the hypotheses that you have.
Mr. Chad Fowler wrote about the hiring issue that you mentioned in his books.
@book{Fowler2010,
Address = {Raleigh, {NC}},
Author = {Chad Fowler},
Edition = {Second},
Publisher = {The Pragmatic Programmers},
Series = {Pragmatic Bookshelf: Pragmatic Life},
Title = {The Passionate Programmer: Creating a Remarkable Career in Software Development},
Year = {2010}}
Chapter 2, pages 27-30, and Chapter 5, pages 37-40, describe this.
The first edition of the book was known as, “My Job Went to India: And All I Got Was This Lousy Book.”
The self-motivated software developer who cares about career growth will engage in lifelong learning and professional development, and avoids using systemic/structural and institutional inequity/bias (e.g., racism and anti-immigrant bias/discrimination) to get jobs and promotions.
So, using OCaml primarily for your code base can filter out the not so motivated software developers.
You can borrow/copy the (former) hiring practices of Galois, which develops most of their work in Haskell. They shared resources, and links to open access/content books (e.g., books published under the Creative Commons license), to help applicants for internships and jobs learn more about Haskell.
Another critical issue that many have not shared is how modern C++ (e.g., C++23, C++20, C++17), modern Java (recent versions), modern Python (3.7 and beyond), and modern JavaScript support functional programming features for opertions like map-filter-reduce.
So, if you look at a candidate’s code base, you can figure out if the candidate has experimented with such features in a “programming sandbox” (to try features of a programming language or library/framework/package) or used them extensively in the code base for most projects.
Also, wage remuneration is also the key factor. If you pay software developers and digital integrated circuit (I.C.) designers a lot of money, they will come work for you. Jane Street Capital pays FPGA interns about US$125/hour as a base salary. So, if undergraduate frosh/sophomores have taken an introductory course on digital/logic circuits, and experimented with hardware construction languages (H.C.L.s) or modern hardware description languages (H.D.L.s) for their laboratory assignments, they would be able to apply for the internship.
If they have taken an introductory digital I.C. design course as an undergraduate sophomore/junior, this would make them stand out.
The caveat is to use software development practices, or computational thinking, to improve digital I.C. design. Taking a course on "data structures and algorithms” helps, but using version/revision control (or software configuration management), automated regression testing (or automated regression verification in the context of digital I.C. design), software architecture modeling (UML/SysML can model digital I.C.s), DevOps (used in VLSI/hardware DevOps), working in UNIX-like environments (via OS-level virtual containerization, such as Docker or Kubernetes and their variants like KubeFlow for machine learning - modern AI-powered electronic design automation software use these anyway), and documentation to improve communication about different aspects of the I.C. design project helps a lot.
I mention this since Jane Street Capital created their own H.C.L., Hardcaml, which is based on OCaml. They love people who have experimented with different H.C.L.s and modern H.D.L.s, such as Chisel HDL (based on Scala), Clash (based on Haskell), and PyMTL/PyRTL/PyGears/PyLog (based on Python).
In the interest of broadening participation, I pay attention to how marginalized and less privileged people work on something in their free time with appropriate timestamps. E.g., if they developed something in 2 hours since they are working 20+ hours per week while maintaining a 4.0 G.P.A. at a decent/competitive research university, I will assess that accordingly. More privileged people should be able to find time to put in more work, and use better tools/frameworks/libraries/platforms/paradigms. That way, you can have diverse teams who can look at problems or issues from another perspective, and avoid common mode/cause failure.