Thanks to Nawaf Bou-Rabee's comments, I can post a first answer. Specifically, Theorem 2.2.1 of [Cerrai '01] seems to state the following - although it is hard to say for certain that I have interpreted all the notations correctly as Google isn't giving me access to the whole book!

> Take $M=\mathbb{R}^d$, take $\ast$ to be Itô, take $k \leq d$ [I guess this probably isn't necessary, but it looks like the book is taking $k=d$, which automatically generalises to $k \leq d$], and let $\sigma(x) \in \mathbb{R}^{d \times k}$ be the matrix formed by horizontally concatenating the vectors $\sigma_1(x),\ldots,\sigma_k(x)$. Let $\|\boldsymbol{\cdot}\|$ denote the operator norm where Euclidean spaces $\mathbb{R}^d$ and $\mathbb{R}^k$ are equipped with the standard Euclidean norm. Suppose that:
>
> 1. There exist values $r_b \geq r_\sigma \geq 0$ such that
> \begin{align*}
 \sup_{x \in \mathbb{R}^d} \frac{|b(x)|}{1+|x|^{2r_b + 1}} &< \infty \\
 \sup_{x \in \mathbb{R}^d} \frac{\|\sigma(x)\|}{1+|x|^{r_\sigma}} &< \infty
 \end{align*}
> and for some $a,\gamma>0$ and $c \in \mathbb{R}$, every $x,y \in \mathbb{R}^d$ has
> $$ (b(y)-b(x)) \boldsymbol{\cdot} (y-x) \leq -a|y-x|^{2m+2}+c(|x|^\gamma+1)\text{.} $$
> 2. For each $p \geq 1$ there exists $c_p \in \mathbb{R}$ such that every $x,y \in \mathbb{R}^d$ has
> $$ (b(y)-b(x)) \boldsymbol{\cdot} (y-x) + p\|\sigma(y)-\sigma(x)\|^2 \leq c_p|y-x|^2\text{.} $$
>
> Then the SDE has a stationary probability measure.

**Reference:**  
[Cerrai '01] S. Cerrai, *Second Order PDE's in Finite and Infinite Dimension: A Probabilistic Approach*, Lecture Notes in Mathematics 1762, Springer-Verlag Berlin Heidelberg, 2001.