AI/ML Intern
@ WillHire

Hybrid
€39,520
Hybrid
Intern
Posted 5 hours ago

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Job Details

About WillHire

WillHire is a modern staffing and talent acquisition platform helping leading organizations find exceptional talent. We’re now expanding into the AI/ML vertical and are looking for curious, driven, and analytical minds to join us as part of our AI/ML Internship Cohort.

Role Overview

As an AI/ML Intern at WillHire, you will collaborate with our engineering and strategy teams to design data-driven solutions that power smarter hiring, workforce planning, and operational decision-making. This is a hands-on role where you’ll work on real business datasets to build production-ready analytics models and dashboards.

Key Responsibilities

  • Collect, clean, analyze, and transform HR and recruitment datasets.
  • Build predictive models for talent forecasting and attrition risk.
  • Develop data visualizations, dashboards, and reports using Python, SQL, and BI tools.
  • Perform exploratory data analysis to uncover recruitment insights.
  • Handle time-series and cohort data for trend and performance analysis.
  • Deploy statistical and ML algorithms in scalable pipelines.
  • Communicate findings and recommendations to stakeholders clearly.

Requirements

  • Pursuing or recently completed B.Tech/BE/M.Tech/MSc in Data Science, Computer Science, Statistics, or related fields.
  • Proficiency in Python and core libraries (Pandas, NumPy, Matplotlib/Seaborn, Scikit-learn).
  • Familiarity with SQL for querying relational datasets.
  • Sound understanding of ML fundamentals including supervised/unsupervised learning methods.
  • Strong statistics foundation covering distributions, hypothesis testing, and probability.
  • Ability to interpret data, derive insights, and present conclusions clearly.
  • Strong communication skills, ownership mindset, and enthusiasm to learn.

Nice to Have (Bonus)

  • Knowledge of BI tools (Power BI, Tableau, Looker, Metabase).
  • Basics of cloud platforms (AWS, GCP, Azure) or Docker.
  • Prior exposure to HR analytics or recruitment datasets.

What You’ll Get

  • Practical exposure to solving real-world data problems in HR Tech.
  • Experience working on high-impact product features used by recruiters and hiring managers.
  • 1:1 mentorship by experienced data scientists and access to premium resources.
  • Internship Certificate and Letter of Recommendation upon successful completion.
  • Opportunity for a Pre-Placement Offer (PPO) at WillHire or client companies.

Hiring Process

  • Online Application: Submit CV, GitHub/Kaggle links, and a brief note on your interest and experience.
  • Technical Assessment: Assignment to test Python, SQL, EDA, or modeling approach.
  • Technical Interview: In-depth discussion (45 mins) on your ML/stats understanding and problem-solving.
  • Managerial Interview: Evaluate communication skills, culture fit, and motivation.
  • Offer: Selected applicants receive the internship offer with stipend details and project allocation.
  • Onboarding: Orientation, project assignment, and setup with tools and mentors.

Stipend

The minimum stipend starts at 19 euro/hour, with the possibility of a higher rate based on interview performance.

Key skills/competency

  • Python
  • SQL
  • Machine Learning
  • Data Analysis
  • Predictive Modeling
  • Data Visualization
  • Exploratory Data Analysis
  • Statistical Analysis
  • HR Analytics
  • Mentorship

How to Get Hired at WillHire

🎯 Tips for Getting Hired

  • Customize your resume: Highlight ML projects and relevant coursework.
  • Showcase your portfolio: Link GitHub or Kaggle projects.
  • Practice technical skills: Prepare for Python, SQL, and modeling assessments.
  • Prepare for interviews: Review ML fundamentals and case studies.

📝 Interview Preparation Advice

Technical Preparation

Review Python data libraries and syntax.
Practice SQL queries on sample databases.
Study ML algorithms and statistical methods.
Work on data visualization using BI tools.

Behavioral Questions

Explain a challenging project experience.
Describe teamwork and conflict resolution methods.
Share examples of self-driven learning moments.
Discuss handling feedback in a project.

Frequently Asked Questions