CEVAL Talents connects you with candidates who have solved real-world coding, data engineering,
and AI/ML challenges inside the CodingEval playground – not just from resumes.
Move beyond resumes and MCQs. Hire using real coding behaviour, lab performance, and problem-solving data.
Shortlist candidates based on actual performance in coding challenges, data pipelines, and SQL labs.
View how candidates reached the solution – attempts, errors, and final optimized version.
Access candidates who have already worked on PySpark, Hadoop, SQL, ML, TensorFlow & PyTorch labs.
Randomized test cases, hidden datasets, and environment monitoring reduce cheating drastically.
Source freshers from CEVAL Campus installations and working professionals via open challenges.
Get per-candidate dashboards: accuracy, speed, attempts, topic-wise strengths and weaknesses.
A streamlined pipeline that converts coding evaluations into hiring decisions.
Compiler • Challenges • Data Labs
Learners and professionals use the CodingEval playground, MCQs, and challenge arena to solve real-world problems across languages and data stacks.
Auto-Graded • Ranked • Tagged
Every submission is scored on correctness, efficiency, attempts, and completion time. Topic tags reveal strengths in DS, SQL, DE, or ML.
Filtered • Ranked Talent Pools
You receive curated, role-ready talent lists with full performance history, code playback, and recommended interview questions.
Structured • Evidence-Based Hiring
Use our recommended interview kits or plug your own rounds. Take decisions backed by actual lab performance, not just gut feel.
Pick from curated talent pools mapped to real tech stacks and job roles.
| Talent Stream | Typical Roles | Key Skills | Sample Use Case |
|---|---|---|---|
| Full-Stack Web | Full-Stack Dev, Web Engineer | HTML, CSS, JS, React/Angular, Node.js, REST APIs | Hiring for product engineering team building dashboards & portals. |
| Data Engineering | Data Engineer, Big Data Engineer | Python, SQL, Hadoop, Hive, Spark, Airflow | Building ETL pipelines for analytics & ML platforms. |
| Data & ML | ML Engineer, Data Scientist | Python, Pandas, Scikit-Learn, TensorFlow/PyTorch, NLP | Recommender systems, churn models, classifier pipelines. |
| Backend & APIs | Backend Engineer, API Developer | Java / .NET, Spring Boot, SQL, Microservices | Fintech, SaaS platform backend & integration projects. |
| SQL & Analytics | Data Analyst, BI Engineer | Advanced SQL, Joins, Windows, Views, Reports | Reporting, dashboards, ad-hoc data analysis teams. |
Ideal for startups & small teams looking for 2–3 strong hires per quarter.
Best for growing product companies & service firms with recurring hiring needs.
End-to-end hiring pipeline aligned with your tech stack, JD templates, and campuses.
Share your hiring requirements and we’ll curate a short list of candidates backed by real CodingEval performance.