joblib hangs if job segfaults

joblib_killer.py

import numpy as np
from sklearn.ensemble import gradient_boosting
import time
 
from joblib import Parallel, delayed
 
class Bad(object):
    tree_ = None
 
 
def fit_one(i):
    if i == 3:
        # this will segfault
        bad = np.array([[Bad()] * 2], dtype=np.object)
        gradient_boosting.predict_stages(bad,
                                         np.random.rand(20, 2).astype(np.float32),
                                         1.0, np.random.rand(20, 2))
    else:
        time.sleep(1)
    return i
 
 
out = Parallel(n_jobs=4)(delayed(fit_one)(i) for i in range(10))
print out