A Worked Example: Hiring an Overseas ML Engineer, Deel vs Remote

You've found a candidate in Poland with the right transformer and MLOps background. The offer needs to close fast because competing AI shops are hiring the same skill set. Deel's same-day contract execution lets you get a signed agreement in front of the candidate within hours of a verbal yes, which matters when a competing offer could land the same week.

Before this engineer touches anything, they need access to client model checkpoints, a cloud training environment and, in most engagements, API keys to third-party model providers. That access is the real exposure, more than the salary or the platform fee. Whichever EOR you use, gate access behind a signed confidentiality and IP assignment agreement executed before, not after, credentials go out. Remote's entity-owned employment model gives you a cleaner argument that IP created during the engagement, including fine-tuned models and prompts, assigns cleanly to your company rather than passing through a staffing intermediary.

Before the engineer touches client systems, work through these steps in order:

1. Get the confidentiality and IP assignment agreement signed before any credentials are issued, and confirm its wording covers model weights, training data and prompts.
2. Limit access to the specific client checkpoints, cloud training environment and model provider keys the engagement actually needs.
3. Record who has access to which client's data and models, tied to their employment status, so you can answer a client's access request quickly.
4. Build a same-day credential revocation step for cloud environments, model APIs and shared client systems into every departure.

Sophisticated clients in this space increasingly ask for a list of everyone who touched their data or models, plus how each person is employed. 'A contractor paid through a payment platform' is a weaker answer than 'a direct employee under a written IP and confidentiality agreement.' If your client base skews toward enterprises with security review processes, that question alone can push the decision toward Remote regardless of onboarding speed.

Once the engagement is stable, you're likely hiring a second and third person, maybe a data engineer and a prompt engineer, possibly in different countries. Cost-per-hire for a nonexecutive role runs around $1,200 on average¹, which adds up as headcount grows. This is the point to decide whether your agency standardizes on one EOR platform for all technical roles or keeps splitting by sensitivity: Deel for faster-moving support and ops roles, Remote for anyone with model or client-data access.

Neither platform reviews your actual data handling practices, model security or whether you're contractually allowed to fine-tune a client's model on data from another client's engagement. That's a governance question for your own team, not something an EOR checks on your behalf.

Most AI services contracts now require you to disclose subprocessors, meaning anyone who touches client data on your behalf, including overseas staff. Keep a current list of who has access to which client's data and models, tied to their employment status, so you can respond to a subprocessor disclosure request without scrambling. This list is also the first thing a client's security team asks for if there's ever an incident, and having it ready ahead of time is far better than reconstructing it under pressure.

It's tempting to quote a client rate based on a rough sense of what an ML engineer costs, then figure out staffing afterward. Work backward instead: price in the base salary, the EOR platform fee, statutory employer contributions in the hire's country, and a margin buffer for the inevitable scope changes AI engagements tend to have. Agencies that skip this step often discover mid-engagement that the staffing cost is eating more of the contract margin than expected, right around the time the client is asking for more scope, not less.

AI implementation work often turns into an ongoing managed-service relationship once the initial build is live, and that's the point to revisit the original staffing decision. An engineer who started on a fixed-term contractor agreement for a defined build might make more sense as an EOR employee once the relationship becomes indefinite retainer work. Treat the six-month mark as a checkpoint: review whether the original classification and platform choice still fit the actual working relationship, rather than letting a contract quietly roll over year after year without anyone rechecking it. That checkpoint is also the natural moment to renegotiate scope and pricing with the client, since the engagement has proven out.