Let's modify the problem slightly, considering instead a $1$-variable strictly convex monic polynomial $P(x)=x^n+a_{n-1}x^{n-1}+\cdots+a_0$ and $\lambda_P(\alpha)=|\{x\in\mathbb R: P(x)<\alpha\}|$. Since $P$ is strictly convex, any line intersects it at most twice including the line $y=\alpha$. In fact, it is easy to see that $P$ has even degree and thus $y=\alpha$ intersects $P$ at exactly two points for $\alpha>M$ the global minimum. Let $m$ be the unique value such that $P(m)=M$. Then we have two functions $f_1(\alpha)< m Generalizing the original problem, let $P(x_1,\ldots,x_k)$ be a strictly convex polynomial in arbitrarily many variables. Let $\chi_P(x_1,\ldots,x_k)$ be the indicator function for the set $\{(x_1,\ldots,x_k):P(x_1,\ldots,x_k)<\alpha\}$. By Fubini's theorem, $$\lambda_P(\alpha)=\int_{\mathbb R^n} \chi_P(x_1,\ldots,x_k)dx_1\cdots dx_k=\int_{\mathbb R}\cdots \int_{\mathbb R} \chi_P(x_1,\ldots,x_k)dx_1\cdots dx_k$$ and note that $\chi_P(x_1,\ldots,x_k)$ is the indicator function of a set $\{x_1: f(x_1)<\alpha\}$ where $f$ is a polynomial with coefficients varying smoothly in the other varaibles. It follows that the roots $f_1,f_2$ are smooth functions of $\alpha,x_2,\ldots,x_k$ except where the relevant Jacobian is noninvertible, which by strict convexity corresponds to points at which $f_1,f_2$ fail to exist and so $f_1,f_2$ are smooth wherever they are defined. Since $$\lambda_P(\alpha)=\int_{\mathbb R}\cdots \int_{\mathbb R} (f_2(\alpha,x_2,\ldots,x_n)-f_1(\alpha,x_2,\ldots,x_n)) dx_2\cdots dx_k$$ it follows by differentiating under the integrals that $\lambda_P$ is smooth.