Machine Learning and Data Science AI Training Interview Questions

Machine learning and data roles ask specialists to analyse data, build evaluation tasks and judge model reasoning on statistics, modelling and code. Screenings tend to probe whether you can explain trade-offs clearly, not only compute them. These practice questions cover the common ground.

18 open roles in this groupUpdated 9 October 2026

Practice questions

These are practice questions written for this site to help you prepare. No platform has said it asks these exact questions.

Explain overfitting and two ways to detect it.
A good answer covers: Model fits noise in training data; detect with a held-out validation set and learning curves. Mention regularisation or more data as fixes.
How would you evaluate a classifier on imbalanced data?
A good answer covers: Precision, recall, F1, PR curves, confusion matrix; accuracy alone is misleading. Tie the metric to the cost of errors.
A model's answer to a statistics question uses the wrong test. How do you explain the error?
A good answer covers: Name the correct test, the assumption that was violated, and how the conclusion changes.
Write a SQL query to find the top customer by revenue per month.
A good answer covers: Correct grouping, window function or subquery, ties handled, and a note on time zones or nulls.
What is the difference between RLHF and supervised fine-tuning?
A good answer covers: SFT trains on example answers; RLHF trains a reward model from human preferences and optimises the model against it.
How would you design an evaluation set for a data analysis assistant?
A good answer covers: Realistic tasks with known answers, varied difficulty, data files, and a rubric for partial credit.
Explain a p-value to a manager.
A good answer covers: Plain words: how surprising the data would be if there were no real effect; not the chance the result is true.
How do you check a dataset before trusting an analysis?
A good answer covers: Missing values, duplicates, outliers, units, date ranges and how the data was collected.
Describe a project where your analysis changed a decision.
A good answer covers: Context, method, result, and the decision it led to, with a number if possible.

What the platforms say about the assessment

In the 2026-10-09 data, roles in this group came from micro1, Meridial, SME Careers and Terac. Each platform runs its own process, and steps can differ by role. Below is what each platform's public pages or postings say, followed by lines quoted from current postings in this group.

micro1

micro1's experts page describes four steps: apply for opportunities, take the AI interview, get onboarded, start earning.
Postings commonly list screening questions, then an AI interview, then in some roles a technical assessment, then a review by the hiring manager. Interview lengths stated in postings range from about 10 to 30 minutes.
Some postings ask you to complete the interview and assessment without outside assistance.
micro1's FAQ says certification does not guarantee immediate placement on a project.

Source: www.micro1.ai

Meridial

Meridial postings describe the work and requirements but do not describe the screening steps.
Postings say contractors supply their own secure computer and internet connection, and recording roles add a high-quality microphone and recording setup. Company benefits such as health insurance do not apply.
We could not confirm Meridial's selection steps from a public page; treat the posting itself as the guide.

Source: boards-api.greenhouse.io

SME Careers

Many SME Careers postings state: 'Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.'
Many postings also say there is no immediate project for the role, and that qualified applicants will be contacted first when relevant opportunities arise.

Sources: sme.careers, api.sme.careers

Terac

Terac's expert docs describe signing in with LinkedIn, verifying your phone, connecting LinkedIn or adding a resume, and a short voice conversation of about 10 minutes that the docs say you can skip and take later.
Each opportunity then has its own steps, usually screening questions followed by the tasks themselves. Research postings describe remote video or voice interviews of 30 to 90 minutes.

Source: terac.com

Quoted from current postings

"Apply to the role and complete the screening questions."
ML Engineer, micro1

"Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter."
Data Scientist Team Lead, sme

"Complete an AI interview of approximately 30 minutes."
ML Engineer, micro1

Steps were read from public pages and postings, not tested first-hand. Passing a screening does not guarantee a project, hours or pay.

Terms to know

RLHF: A way of improving a model by having people compare or score its answers, training a reward model on those judgements, then tuning the model to produce answers people prefer.
SFT: Training a model on examples of good prompts and ideal answers written or checked by people, so it learns the expected format and quality.
Reward model: A separate model trained on human preference judgements that predicts how a person would score an answer. It is used to steer the main model during RLHF.
Benchmark: A fixed set of test tasks used to compare models or track progress over time.
Model evaluation: Testing how well a model performs on a set of tasks, often by people scoring answers against a rubric.

Open roles in this group (18)

Senior Data Analyst micro1 $50-80/hr as listed Referral
Data Analyst (AI Evaluation) micro1 $30-60/hr as listed Referral
Data Science Specialist micro1 $150-350/hr as listed Referral
Computer Vision QA Specialist SME Careers Up to $2.5/hr as listed
Research Engineer - Code Generation & Model Evaluation micro1 $50-100/hr as listed Referral
ML Engineer micro1 $80-150/hr as listed Referral
Data Analyst micro1 $31-60/hr as listed Referral
Machine Learning (ML) AI Task Auditor - Freelance AI Trainer Project Meridial $60/hr as listed
Machine Learning Engineers: Scenario Building for Reinforcement Learning Terac $90/hr as listed
Data Scientist micro1 $245-280/hr as listed Referral
Data Analyst micro1 $50-60/hr as listed Referral
Data Scientist Team Lead SME Careers Up to $110/hr as listed
Data Scientist SME Careers Up to $100/hr as listed
Machine Learning Engineer micro1 $80-140/hr as listed Referral
Big Data Engineer micro1 $30-80/hr as listed Referral
ML Engineer Specialist - Freelance AI Trainer Project Meridial $30-50/hr as listed
Computer Vision Specialist - Freelance AI Trainer Project Meridial $8-65/hr as listed
Data Science Specialist - AI Trainer Project- Freelance AI Trainer Project Meridial $6-65/hr as listed

Machine Learning and Data Science AI Training Interview Questions

Practice questions

Explain overfitting and two ways to detect it.

How would you evaluate a classifier on imbalanced data?

A model's answer to a statistics question uses the wrong test. How do you explain the error?

Write a SQL query to find the top customer by revenue per month.

What is the difference between RLHF and supervised fine-tuning?

How would you design an evaluation set for a data analysis assistant?

Explain a p-value to a manager.

How do you check a dataset before trusting an analysis?

Describe a project where your analysis changed a decision.