The metric can be thought of as a linear map between two vector spaces, but they're not the same vector space. Rather, we can think of the metric as a map from $V \to V^*$, the dual space of the original vector space $V$. If you've never encountered a dual space $V^*$ before, it is defined as the set of all linear maps from a vector space $V \to \mathbb{R}$. (Or to $\mathbb{C}$ if we're talking about complex vector spaces, as in quantum mechanics.) It is not too hard to see that the space of all maps $V \to \mathbb{R}$ is itself a vector space: there is a zero map, the sum of two maps is also a map, we have a notion of scalar multiplication, etc. So $V^*$, so defined, is a vector space.
The metric $g$ is defined as a bilinear function from $V \times V \to \mathbb{R}$. But the presence of a metric also defines a correspondence between $V$ and $V^*$, as follows: for any element $v \in V$, define the corresponding element $v^* \in V^*$ as the map $v^*(w) \equiv g(v,w)$. It is not too hard to see that $v^* \in V^*$; since $g$ is bilinear, it is a linear map from $V \to \mathbb{R}$.
What's more, this correspondence map is in fact a linear isomorphism between $V$ and $V^*$:
- The correspondence map is linear, since the map $(\alpha v)^*$ maps $w \to g(\alpha v, w) = \alpha g(v,w)$, and so it is equal to the map $\alpha (v^*)$. Similarly, it is not hard to show that $(u + v)^* = u^* + v^*$.
- The correspondence map is one-to-one, since if we have two elements $u,v \in V$ such that $u^* = v^*$ then we must have $g(u, w) = g(v,w)$ for all $w \in V$, meaning that $g(u - v, w) = 0$ for all $w$. This then implies that $u = v$ because of the non-degeneracy of the metric.
- The correspondence map is onto. This proof is a little trickier, but the easiest way to do it is to define a basis of $n$ vectors $\{v_\mu\}$ for $V$ (where $n = \dim V$), define a set of $n$ dual vectors $\{{v^*}^\nu\}$ by the relation ${v^*}^\nu(v_\mu) = \delta^\nu {}_\mu$, and then show that these vectors form a basis for $V^*$, establishing that $\dim V = \dim V^*$.
So you can think about the metric as a linear isomorphism from one basis to another, but the catch is that the bases in question belong to two different vector spaces. In particular, it maps a coordinate basis for $V$) to a corresponding coordinate basis for $V^*$.