Defining pipelines of functions when passing a main argument across multiple functions
Without being familiar in use of sklearn, there are still some Python fundamentals that can be improved:
Superfluous comprehension
func_args = [k for k, v in inspect.signature(func).parameters.items()]

can probably be
func_args = inspect.signature(func).parameters.keys()

assuming that parameters has the interface of a regular dictionary. Also, since you're only using it to test membership, wrap it in a call to set().
Set intersection
If you do the above and make func_args a set, then this:
for k in dict(kwargs) if k in func_args

can be replaced by set(kwargs.keys()) &amp; func_args.
Non-repeatable read
There's a potential issue with your use of pop(). This modifies your kwargs in a loop. Are you sure that you want a given kwarg to only apply to one function in your pipe, and not all of them?
Real tests
Convert this:
example_pipe= create_sequential_pipe([example_func_1, example_func_2, example_func_3])

out = example_pipe(2)
print(out)  # 2.0

out = example_pipe(2, power=2, sum=1, divide=5)
print(out)  # 1.0

into an actual unit test - you're already most of the way there, so you might as well.
Variadic function
create_sequential_pipe(func_list):

is a good candidate for being turned into a variadic function, i.e. accepting *func_list. This will make invocation simpler in some cases, including the one you showed at the bottom - there will be no need for an inner list literal.