Domain-Specific AI Assessments

Codeaid offers a variety of test types you can tailor to your needs, including multiple choice, open-ended questions, and coding tasks. Assessments cover Traditional ML, Deep Learning, Generative AI, NLP, and Computer Vision, auto-scored on model accuracy and code quality.

Evaluate candidates on real AI skills, not just theoretical knowledge.

Realistic Test Room with Notebooks & Containers

Test takers work in realistic environments, from interactive notebooks (JupyterLite) to GPU-powered containers, mirroring actual on-the-job execution. They handle data, build models, debug pipelines, and improve performance in practice.

Assess how candidates perform in the same setup they'd use on the job.

AI Interviewer for Quick Assessment Creation

Codeaid's AI Interviewer helps you create assessments tailored to your hiring or training validation needs. Choose from expert-designed interviews and datasets, or generate your own from scratch. It defines questions, adjusts difficulty levels, and generates realistic ML and AI assessments in minutes.

Create custom assessments quickly without manual effort.

Messy, Real-World Datasets

Codeaid provides messy, real-world datasets that make the difference in understanding whether test takers can actually handle real AI engineering work. Datasets are large and complex enough that they cannot be fed into an AI tool — every answer reflects the test taker's own ability.

Prevent AI cheating and get authentic evaluations.

Comprehensive Structured Evaluation Reports

Once the assessment is submitted, Codeaid analyzes the test taker's work and generates structured evaluation reports in real time. Review insights on code quality, model performance, problem-solving approach, and engineering decisions.

Clearly understand each test taker's real AI engineering ability.

Built for Teams Developing and Hiring AI Engineers

Codeaid helps organizations run coding assessments and online coding tests for AI and ML engineering roles — from initial screening to final technical evaluation. It supports upskilling internal engineers and hiring AI engineers at speed.

Streamline your entire AI talent evaluation process.

• Domain-specific AI assessmentsCodeaid offers assessments across Traditional ML, Deep Learning, Generative AI, NLP, and Computer Vision, designed to reflect real-world workflows.
• Realistic testing environmentTest takers work in interactive notebooks or container-based setups, mirroring actual on-the-job execution for AI engineering tasks.
• Auto-scoring on model accuracy and code qualityAssessments are automatically scored based on model accuracy and code quality, reducing manual grading effort.
• Built for AI/ML hiringThe platform is specifically designed for companies hiring machine learning engineers, data scientists, and AI developers, with features like candidate screening at scale.

• Pricing detailsPricing starts at $129 per month for the Team plan with 5 users and 20 candidate invites per month, but exact pricing for Enterprise and credit packs is not fully detailed on the page.
• IntegrationsThe Team plan lists Recruitee, Greenhouse, and SmartRecruiters integrations, but the Enterprise plan's integrations are not explicitly listed in the scraped content.
• AI interviewer functionalityThe page mentions an 'AI interviewer' and a link to learn how it works, but the scraped content does not provide details on how it operates or its capabilities.
• Assessment content specificsWhile the page mentions assessments across various domains, the exact number of questions per interview (75 for Team) and custom templates (2 for Team) are only shown for the Team plan; Enterprise details are not fully specified.

Hiring AI Engineers

Codeaid is built for companies hiring machine learning engineers, data scientists, and AI developers. It lets you run domain-specific coding assessments covering Deep Learning, Generative AI, NLP, and Computer Vision, with auto-scoring on model accuracy and code quality. You can screen candidates at scale and make faster hiring decisions without scheduling technical interviews.

Upskilling Internal Engineers

For companies transitioning software engineers into AI and ML roles, Codeaid's technical assessment platform identifies skill gaps across your existing team and structures a clear path from software engineering to ML engineering. It helps you evaluate real skills, not theoretical knowledge, and supports developing your existing team.

Training Validation

Codeaid takes the guesswork out of training and upskilling ML engineers with assessments across Deep Learning, Generative AI, NLP, and Computer Vision. You can create assessments tailored to your training validation needs, using expert-designed interviews and datasets or generating your own from scratch with the AI Interviewer.

Evaluating Real-World AI Workflows

Codeaid enables teams to evaluate AI engineers through domain-specific challenges that reflect real-world workflows, not theoretical exercises. Test takers work in realistic environments—from interactive notebooks to GPU-powered containers—allowing you to assess how they handle data, build models, debug pipelines, and improve performance in practice.

Sign up for a free Codeaid account and install the IDE plug‑in.

Connect the plug‑in to your repository to enable context awareness.

Choose a plan that matches your team size and enable private model hosting if needed.

Start coding—watch AI suggestions appear and refine them as you go.