Deep Learning Intern

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Skills you'll use

What you'll do

• Design and train CNN, RNN and Transformer architectures
• Optimise models for GPU training speed and inference latency
• Run ablation studies and hyper-parameter searches
• Reproduce results from state-of-the-art research papers
• Document architectures, experiments and learnings
• Document work clearly and act on feedback

Who can apply

• Pursuing or recently completed a degree in CS/IT/Statistics/Maths/Data Science or related
• Foundational knowledge of Python, Deep Learning, PyTorch, TensorFlow
• Strong analytical thinking, communication and a proactive attitude
• Ability to work in a team and meet deadlines
• Based in or open to working from Bengaluru

Perks & benefits

Interview & selection process

4 rounds — typical selection flow for this role:

1. 1The selection process for the Deep Learning Intern at Pine Labs is structured, merit-based and typically involves 4 evaluation rounds followed by an HR discussion (about 5 stages in total): Round 1: Online Application & Resume Screening — apply through the verified link on this page; profiles are shortlisted on fundamentals and fit Round 2: Online Assessment / Aptitude — a test covering statistics, SQL, Python and basic deep learning concepts Round 3: Technical Interview 1 — core data-science fundamentals: statistics, Python, Deep Learning, PyTorch and problem-solving Round 4: Technical Interview 2 / Case Study — a hands-on data/ML case or take-home task discussion with the team Round 5: HR Discussion — role expectations, stipend, start date and offer The process is designed to assess your fundamentals, problem-solving ability and communication rather than rote knowledge. There are no charges at any stage. Shortlisted candidates are contacted through the official careers channel after they apply via the link on this page.

About Pine Labs

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