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Hiring now · posted 3d ago Tech Contract · On-site / hybrid

Scientific / ML Engineer

$90–$140/hr

Published pay. The final rate depends on your test, experience and country.

United States Language: English Posted 9 Nov 2026

Scientific / ML Engineer is AI-training work for data scientists, paying $90–$140/hr, open to applicants in United States. Posted 9 Nov 2026, still open on 13 Nov 2026. Zekai lists it for free; the application goes to the employer's platform.

About this role

Preparing for this role? See the best AI tools for data scientists, practise with ready-made prompts for data scientists, read How to Use AI for Data Cleaning: A Step-by-Step Guide (2026) and take the free 30-day AI challenge.

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models.

1. Overview

Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're seeking talented Machine Learning Engineers and Scientific Computing experts with hands-on expertise in machine learning, deep learning frameworks and scientific computing to bring hands-on technical and research excellence and elevate the quality of our AI training data.

This is a W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI Lab as part of their extended workforce.

2. Key Responsibilities
  • Guide research and engineering teams to close knowledge gaps and improve AI model performance in machine learning and scientific computing, model training and evaluation, and numerical and scientific software topics.
  • Design challenging, domain-relevant tasks, and write accurate and well-structured solutions to machine learning and scientific computing problems.
  • Evaluate machine learning and scientific computing tasks and solutions and provide clear, written technical feedback.
  • Design and evaluate technical tasks covering model training, experiment design, data pipelines and scientific simulations, with runnable reference solutions.
  • Develop rubrics to assess the methodological soundness, correctness and reproducibility of ML and scientific work.
  • Collaborate with other subject matter experts to ensure consistency and accuracy in training data.
3. Core Qualifications
  • 4+ years of dedicated professional or research experience in machine learning, data science or scientific computing at a recognized, top-tier organization or research university (an MS or PhD in a quantitative field counts toward this).
  • Production or research experience with PyTorch, JAX or TensorFlow, and strong Python (NumPy, pandas, scikit-learn).
  • Publications, open-source contributions or shipped ML systems are a strong plus.
  • Demonstrable career progression.
  • Ability to engage reliably for at least 20 hours/week during weekdays.
  • Strong written communication skills and the ability to explain complex technical decisions clearly.

About Cincinnatus LLC: Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives.

Equal Employment Opportunity: Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic.

Location: United States.

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  3. Most platforms ask for a CV and a short skills test or AI interview in your field.
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Your plan for “Scientific / ML Engineer”

What to know before you apply

Pay
At the published rate, 10 hours a week would be about $900–$1,400 and 20 hours about $1,800–$2,800 before tax. Hours depend on the project, so treat this as a ceiling, not a promise.
Location
Only applicants located in United States can be paid for this role. Platforms usually verify where you are, so apply only if you are based there.
Credentials
The listing asks for a PhD, 4+ years of experience. Put it in the first line of your profile: reviewers screen for it before anything else.
Test tips for data scientists
  • Check data leakage, metric choice and baselines before anything else.
  • Rebuild key numbers in a notebook when you can.
  • Explain trade-offs in plain language; reviewers value clarity.
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