  FreezeML is a new approach to first-class polymorphic type inference that
employs term annotations to control when and how polymorphic types are
instantiated and generalised. It conservatively extends Hindley-Milner type
inference and was first presented as an extension to Algorithm W. More modern
type inference techniques such as HM(X) and OutsideIn($X$) employ constraints
to support features such as type classes, type families, rows, and other
extensions. We take the first step towards modernising FreezeML by presenting a
constraint-based type inference algorithm. We introduce a new constraint
language, inspired by the Pottier/R\'emy presentation of HM(X), in order to
allow FreezeML type inference problems to be expressed as constraints. We
present a deterministic stack machine for solving FreezeML constraints and
prove its termination and correctness.
