Q:

Can I write estimate $\pm$ its standard error? 

Suppose I have an MLE estimate $\hat{\theta}$ for a parameter $\theta$, and $\hat{\sigma}$ is the sqrt of the inverse of the negative of the Hessian of the log likelihood at $\hat{\theta}$. Can I write $\hat{\theta} \pm \hat{\sigma}$? 
In general, if I have an estimate $\hat{\theta}$ for a parameter $\theta$, and an estimate $\hat{\sigma}$ of the standard deviation of $\hat{\theta}$, can I write $\hat{\theta} \pm \hat{\sigma}$?  Will others understand what I mean?  Is it also what others write? 

A:

It's fairly common, but not standard enough that it needs no explanation.  $\hat\theta\pm 1.96 \hat\sigma$ is also common—an (approximate perhaps) 95% confidence interval. 

A:

I think it depends what you want to convey.  
To report the standard error or your estimate you could just write $\hat{\theta} (\hat{\sigma})$. This notation is quite common in the statistical literature, but for the sake of clarity you might mention that the standard error is in parenthesis/brackets the first time you use this notation. 
To provide a confidence interval with your estimate you might want to write $\hat{\theta} \pm z_{\alpha/2}\hat{\sigma}$, where $z_{\alpha/2}$ is the quantile of the standard normal distribution and $1-\alpha$ the confidence level of your choice.  A common choice is $\alpha = 0.05$ leading to $\hat{\theta} \pm 1.96\hat{\sigma}$.
The second option is a much stronger statement.  In addition of providing the standard error of the estimate, it gives a confidence interval relying on the normality of the MLE, which might be too coarse in finite samples: it might include invalid parameter values (e.g., probabilities larger than one), and/or wrongly imply that the confidence interval is symmetric.