Shruti Sarkar

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Shruti Sarkar

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Shruti writes at the crossroads of AI, ethics, and the future of hiring. With a background in both engineering and philosophy, they challenge assumptions in how we assess and select talent.
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Introducing HackerEarth OnScreen: AI-powered interviews, around the clock

Introducing HackerEarth OnScreen: AI-powered interviews, around the clock

Tech hiring has a blind spot, and it's not the resume pile, the take-home tests, or even the interview itself. It's the gap between when a great candidate applies and when your team is available to talk to them. That gap costs you more top talent than any competitor does.

Today, HackerEarth OnScreen closes it permanently.

The real cost of scheduling friction

Most companies assume they lose candidates to better offers. The data tells a different story.

A developer weighing two opportunities almost always moves forward with the company that responded first, not the one that sent a calendar invite for Thursday. AI-generated resumes have flooded inboxes, making screening harder. Engineering teams the people best positioned to evaluate technical depth have limited hours. Recruiters are under pressure to move faster while maintaining quality.

Something had to change.

What OnScreen does

OnScreen doesn't just automate scheduling. It conducts the interview.

A candidate who applies at 11 PM gets a full interview before Monday morning through lifelike AI avatars with built-in identity verification and proctoring. The experience is a genuine two-way conversation: dynamic, adaptive, and role-calibrated. This is not a chatbot filling out a scorecard.

One enterprise customer screened more than 2,000 candidates in a single weekend with complete consistency and zero interviewer bias.

"Recruiters are under pressure more than ever. The volume of applicants has surged, AI-generated resumes have made initial screening harder, and the risk of missing the right candidate keeps climbing. OnScreen was built so that no qualified candidate is overlooked because nobody was available to interview them."
— Vikas Aditya, CEO, HackerEarth

Three capabilities, combined for the first time

In-depth interviewing that evaluates reasoning, not recall.
OnScreen conducts dynamic technical conversations that adapt to how each candidate responds. It probes the depth of knowledge, follows threads, and evaluates the quality of thinking behind each answer not just whether the answer is correct. Every interview runs on a deterministic framework: the same structure for every candidate and no panel-to-panel variation.

Integrated proctoring, built in from the start:
Enterprise-grade proctoring is woven directly into the interview flow not bolted on as an afterthought. Legitimate candidates won't notice it. The ones who shouldn't be in your pipeline will.

KYC-grade candidate verification
OnScreen brings identity verification standards from financial services into technical hiring. Proxy candidates, resume misrepresentation, and skills that don't match the application – all three gaps were closed at the source.

What hiring teams are saying

"Before OnScreen, we had no reliable way to measure candidate quality, especially with the rise of AI-generated CVs. Now, screening is far more objective. Roles that previously took much longer are now being closed within three to four weeks."
— Pawan Kuldip, Head of Human Resources, Discover Dollar Inc.

Built for everyone in the process

For engineering teams:
Fewer hours on screening calls. Senior engineers focus on final-round conversations, not first-pass filters.

For recruiters:
Pipelines that move. Candidates evaluated and scored before the week starts.

For candidates:
A consistent, skills-first experience, regardless of when they apply or where they're located.

OnScreen integrates directly into HackerEarth's existing platform alongside Hiring Challenges, Technical Assessments, and FaceCode. It extends your interviewing capacity without adding headcount.

The hiring bar just got higher. Everywhere.

Top talent expects swift, fair processes. Companies that deliver both, at scale, around the clock, will hire the engineers everyone else is still scheduling calls about.

OnScreen is now live for enterprise customers. Request access at hackerearth.com/ai/onscreen.

HackerEarth powers technical hiring at Google, Amazon, Microsoft, and 500+ global enterprises. The platform supports 10M+ developers across 1,000+ skills and 40+ programming languages.

20 Machine Learning/Artificial Intelligence Influencers To Follow In 2024


Currently employed as the Director of Machine Learning in the Special Projects Group at Apple Inc., Ian Goodfellow has majorly contributed to the Deep Learning space. He is the inventor of generative adversarial networks, an ML technique that is being used by Facebook. Earlier in his career, he worked with Google, playing a key role in Street Smart (Google Maps) and Google Brain (AI Research) teams. Besides that, he has also co-authored a comprehensive book, Deep Learning, alongside Yoshua Beng and Aaron Courville.



Jason Brownlee11. Jason Brownlee
Follow @TeachTheMachine
With the aim of ‘making developers awesome at Machine Learning’, Jason Brownlee founded the Machine Learning Mastery—a community offering various collaterals to help developers enhance their skills of applied Machine Learning.





Jess Hamrick12. Jess Hamrick
Follow @jhamrick
Currently employed as a research scientist at DeepMind, Jess Hamrick is a cognitive science enthusiast. Her key research area lies in human cognition by combining ML models with cognitive science. She is also one of the key maintainers of Jupyter/nbgrader—an open-source tool used to creating and grading assignments in the Jupyter notebook.



Kirk Borne13. Dr. Kirk Borne
Follow @KirkDBorne
Dr. Kirk Borne, a data scientist and astrophysicist, is one of the leading influencers in the Big Data/Data Science/AI space. He is currently employed as the Principal Data Scientist and Executive Advisor at Booz Allen Hamilton. He has also been a professor of astrophysics and computational science at George Mason University for over twelve years. His work has majorly contributed to various projects including NASA’s Hubble Space Telescope.



Martin Ford14. Martin Ford
Follow @MFordFuture
Martin Ford is a well-acclaimed futurist and a keynote speaker, elaborating on topics such as AI and robotics, and their possible impacts on the market, economy, and society. He is also an author of three books, including the New York Times bestseller, Rise of the Robots: Technology and the Threat of a Jobless Future. He is also the Consulting Artificial Intelligence Expert for the Rise of the Robots Index project for Societe Generale Corporate and Investment Banking.



Mike Tamir15. Mike Tamir
Follow @MikeTamir
Mike Tamir is currently the Chief Machine Learning Scientist and head of ML/AI at Susquehanna International Group, LLP (SIG). He is also a Data Science faculty member at UC Berkeley. Prior to this, he served as the Head of Data Science at Uber Advanced Technologies Group, and as the Chief Science Officer at Galvanize Inc. Earlier in his career, he was a faculty member at the University of Pittsburgh and Columbia University.



Oriol Vinyals16. Oriol Vinyals
Follow @OriolVinyalsML
Oriol Vinyals is employed as a Principal Research Scientist at Google DeepMind, leading the Deep Learning team there. He has also led the AlphaStar team that developed the first AI that defeats the top professional players of the game, StarCraft. In the past, he was a Senior Research Scientist in the Google Brain team.



Peter Skomoroch17. Peter Skomoroch
Follow @peteskomoroch
Presently serving as a senior executive and investor for numerous ML-driven startups and venture capital funds, Peter Skomoroch has over twenty years of experience in the Data Science industry. Over the years, he has worked as a Senior Research Engineer at the AOL Search Analytics team, Director of Analytics at Juice Analytics, Principal Data Scientist at LinkedIn, CEO and Co-founder of SkipFlag, and Head of AI Automation & Data Products at Workday, among various other roles. At LinkedIn, he played a key role in ideating, creating, and deploying LinkedIn Skills and Endorsements.



Soumith Chintala18. Soumith Chintala
Follow @soumithchintala
Soumith Chintala has co-created and led PyTorch, an open-source Machine Learning library developed by the Facebook AI Research lab for Computer Vision and Natural Language Processing applications. Having worked in the past on projects such as Google Street View House Numbers, pedestrian detection, sentiment analysis, and at New York University, he is also an extensive researcher in the ML space.



Yann LeCun19. Yann LeCun
Follow @ylecun
Yann LeCun is the VP and Chief AI Scientist at Facebook, leading the scientific and technical AI research and development for the organization. In addition, he is a professor at New York University. Early on in his career, he headed the Image Processing Research Department at AT&T Labs Research. Being one of the Godfathers of AI, he has made a huge contribution in the field of Computer Vision and Optical Character Recognition. He is also one of the 2018 ACM A.M. Turing Award laureates for his contribution to the AI domain.



Yoshua Bengio20. Yoshua Bengio

Yoshua Bengio is one of the pioneers in the ML space, owing to his work on artificial neural networks and Deep Learning. He has been a professor in the Department of Computer Science and Operations Research at the Université de Montréal for over twenty-five years. He also heads the Montreal Institute for Learning Algorithms. Yoshua Bengio, Geoffrey Hinton, and Yann LeCun are considered as the Godfathers of AI and have been awarded the 2018 ACM A.M. Turing Award for achieving major breakthroughs in deep neural networks.