AI Workforce · 02 / TLNT
One route to hard-to-fill AI, ML, data, infrastructure, research and STEM talent — delivered through RPO, contingency search, staff augmentation, Employer of Record, contract-to-hire or project-based experts.
The problem
Niche AI and technical profiles rarely surface through ordinary channels — and coordinating recruiters, EoR providers and freelance marketplaces in parallel burns months.
The outcome
One accountable partner for specialized technical talent, routed through whichever hiring model fits the role.
Capabilities
Best fit
Talent routing
RPO, contingency search, staff augmentation, Employer of Record, contract‑to‑hire or a managed pod — one partner, whichever path the role demands.
Direct-hire search for specific roles. We find, vet and hand over finalists to your team — you hire them onto your payroll.
Best forCritical permanent roles and core-team building.
We operate all or part of your hiring function — sourcing, screening, assessment, coordination and offer support — as a long-term managed program.
Best forSustained hiring programs and long-term managed work.
Specialists join your team and work inside your process, while contracts, payments and HR stay on our side.
Best forShort, intense engagements and scaling fast without overhead.
Hire the person you chose — anywhere — without opening a local entity. We become the legal employer and handle payroll, taxes and compliance.
Best forCross-border hiring without a local legal entity.
Start on contract, prove fit in production, then convert to a permanent hire on your terms.
Best forHigh-stakes roles where you want evidence before commitment.
A calibrated pod — evaluators, annotators, engineers or domain experts — delivered as a managed unit against outcomes, or project-based experts for defined scopes.
Best forEvaluation sprints, data programs and defined projects.
Engagement protocol
Share one role, one evaluation workflow or one task package. Nothing more is required to begin.
We match the need to the right delivery model and confirm feasibility, quality bar and coverage.
We start with a first role, sprint or task package — small enough to prove fit fast.
Review results together, tune quality, then scale the model that works.