MLOps Engineer (Model Deployment & Monitoring)

About Precision Federal

Precision Federal is a Christian company. We are a Christian-owned small business building AI, data and software systems for government agencies, and the company is run on Christian principles: every number we publish is real, every claim we make is verifiable, and the work is done with excellence as service to God.

How this role works

1. You join the bench. Before we name you on a proposal that matches this role, we send you the role, the hours and the hourly rate for that bid, and you confirm it in writing. If we don't win, you owe nothing.
2. A contract is awarded. The award funds the team named in the proposal. Your engagement begins, at an hourly rate agreed before you were ever named.
3. You work remote, paid from the contract. ~120–600 hrs per funded award — and if no award ever funds, you owe nothing and lose nothing.

What you'll do

• Build the training, packaging and deployment pipelines for models and LLM applications
• Version data, features, code and model weights so every result can be reproduced
• Monitor models in production for drift, latency, cost and failure, with alerting
• Harden model serving to the customer's security and accreditation baseline

Required qualifications

• Direct experience deploying and operating machine-learning models in production
• Working knowledge of MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML or comparable tooling, and containers
• U.S. citizen or lawful permanent resident (U.S. person)
• Willing to be named on a federal proposal with a one-page resume, and to sign a short letter of commitment

Preferred qualifications

• Kubernetes and infrastructure as code
• GPU inference serving and LLM operations
• Federal cloud environments at FedRAMP Moderate, IL4 or IL5

Compensation & structure

1099 consulting engagement. $60–$100 per hour, confirmed in writing before you are named on any proposal. Hours are funded by federal contract awards — this seat is scoped at roughly 120–600 hours per funded award, fully remote. Work and pay begin only if the contract is awarded — no award, no hours, no obligation.

Apply — MLOps Engineer (Model Deployment & Monitoring)

Every application is read personally by the founder. We respond to every serious one.

First name *

Last name *

Email *

Phone

City & state

Years of relevant experience * Select Under 5 5–10 10–15 15–20 20+

Work authorization * Select U.S. citizen U.S. lawful permanent resident Other

Security clearance Select (optional) None Prior (inactive) Active

Military service Select (optional) None Veteran Retired military Currently serving (Guard/Reserve)

LinkedIn or portfolio link

Resume (PDF or Word) *

How did you hear about us?

Five questions

These are the substance of the application. Answer from your own experience — a few sentences each is plenty, and “this never came up” is a real answer we want.

1. How often did a model nobody could retrain because the data, code and weights were never versioned together come up in your work, and roughly what did it cost — in hours, in people, or in rework? *

2. What tool or process does your organization use today for machine-learning operations, and where does it fall short? *

3. If a better way to handle machine-learning operations existed, which office or role would decide whether to adopt it? *

4. Do you have any role in deciding what tools or systems your organization adopts — approving, evaluating, or recommending a purchase? *

5. Do you own, or hold signing authority for, a company or consultancy of your own? *

May we name you, by name and title, as a proposed consultant on our team in federal proposals, and quote your answers above? * Please choose… Yes No

Submit application

Questions before applying? contact@precisionfederal.com · See all open roles