I encountered the "memory hogging" behavior of Python processes once, where I was sure that my GC worked correctly and that I released all unused objects but still the memory of the process would keep growing. I also remember having this problem with a C++ once as well. It doesn't seem a problem though since the OS should normally release the memory if it's needed by another process. Still, this kind of behavior can…
What do you consider as alternative to celery?
For launching a bunch of IO-bound "tasks", for example calling external services from Django views, I'd consider using Twisted (or Tornado, or asyncio). Your tasks would need to be either written in async style, or you'd need to spawn new processes from within Twisted (but built-in functionality makes this rather easy). Still, Twisted is rock-solid, doesn't leak and is capable of handling a lot of (IO-bound) tasks concurrently.
If your tasks are CPU bound you pretty much have no choice other than something based on multiprocessing. You can still use Twisted, but only in the second way. If the code of your tasks doesn't use C extensions you could use Jython with threads. This way you'd get parallelism without having to rewrite much code.
If you need your tasks parallelized and you want to run a lot of them concurrently then I'm afraid you're out of options in Pythonland. Personally I'd go for Erlang with ErlPort, but I know Erlang rather well.
On the other hand, Celery is a nice piece of code. I think in most cases you don't need anything else, or at least nothing drastically different, like the options above. Perhaps rq would be a good idea. I also encountered an interesting project called Pulsar (http://pythonhosted.org/pulsar/overview.html), but it seems to be usable only on 3.3 and above.