Location
Pune, Maharashtra
Work Mode
Hybrid
Duration
6 months
Stipend
₹39,000/mo
Start Date
Immediate / Rolling
Openings
3 positions
Type
Full-time
Category
Machine Learning
About the Internship
Join Syntel (Atos) in Pune as a Prompt Engineering Intern. This entry-level internship is built for candidates eager to turn classroom knowledge into hands-on, business-facing experience.
As a Prompt Engineering Intern, you will work closely with experienced professionals in a it services…
About Syntel (Atos)
Syntel (Atos) offers a mentor-led Prompt Engineering Intern in Pune with real project work, a stipend of ₹39,000 / month and a Pre-Placement Offer opportunity for strong performers.
See all Syntel (Atos)internships →Pune, MaharashtraVerified employer3 openings
Apply to Syntel (Atos) →Skills Required
Prompt EngineeringLLMsPythonOpenAI APILangChainNLPEvaluationFine-tuning Basics
Who Can Apply
- Students in their final year or recent graduates (Any graduate with strong reasoning; CS a plus) based in or willing to work from Pune, who are curious, self-driven and keen to learn machine learning on real projects. Freshers welcome — a strong project portfolio matters more than prior work experience.
Perks
Networking opportunitiesInternship CertificateLetter of RecommendationMentorship from experienced professionalsReal-world project experiencePre-Placement Offer (PPO) opportunity
Interview & Selection Process
3 rounds — typical selection flow for this role:
- 1Application Screening — the recruitment team at Syntel (Atos) reviews your resume, projects/portfolio and fit for the Prompt Engineering Intern role.
- 2Aptitude / Skills Assessment — a screening test focused on reasoning, writing and basic Python/LLM knowledge.
- 3Technical / Role Interview — an in-depth discussion of your skills, projects and a task or case relevant to machine learning.
- 4HR / Managerial Discussion — a conversation about your interests, availability, learning goals and the internship offer with Syntel (Atos).
₹39,000/month
Stipend · 6 months
Openings3 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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