Location
Bhopal, Madhya Pradesh
Work Mode
In Office
Duration
3 months
Stipend
₹28,000/mo
Start Date
Immediate / Rolling
Openings
15 positions
Type
Full-time
Category
Machine Learning
About the Internship
Start your career in reinforcement learning with CaptiveAire India as a Reinforcement Learning Intern in Bhopal. You will sit with a working team, use the same tools and systems they do, and own a defined piece of work from day one.
About the role
As a Reinforcement Learning Intern at CaptiveAire…
About CaptiveAire India
CaptiveAire India offers a mentor-led Reinforcement Learning Intern in Bhopal with live project work in machine learning, a stipend of ₹28,000/month and a Pre-Placement Offer opportunity for strong performers.
See all CaptiveAire Indiainternships →Bhopal, Madhya PradeshVerified employer15 openings
Apply to CaptiveAire India →Skills Required
PythonReinforcement LearningOpenAI GymPyTorchPolicy GradientsQ-LearningReward DesignSimulationMathematics for MLGit
Who Can Apply
- Final-year students and recent graduates from B.E./B.Tech (CSE/IT/ECE), BCA/MCA or B.Sc/M.Sc (Computer Science / IT) who are based in or willing to work from Bhopal. You should be keen to learn Python, Reinforcement Learning, OpenAI Gym on real projects and able to write clearly. Freshers are welcome — no prior work experience is required, and a strong project portfolio matters more than a long CV.
Perks
Pre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship CertificateLetter of RecommendationDirect access to the team that owns the data you work on
Interview & Selection Process
4 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Technical interview on fundamentals and your projects
- 3Practical assignment or case study with a short walkthrough
- 4HR discussion — stipend, start date, expectations and offer
₹28,000/month
Stipend · 3 months
Openings15 positions
Applicants0 applied
ModeIn Office
CategoryMachine Learning
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