Our Esteemed Client Company

AI/ML Engineer Intern.
Pune
July 1, 2026
Internship PPO

Job Description

Company Name: Our Esteemed Client Company.

(The company name will be disclosed only to shortlisted candidates and will be shared in detail during the Pre-Placement Talk)

Experience: Fresher.

Role: AI/ML Engineer Intern.

Job Location: Pune.

Eligibility Criteria:

  • Qualification: BE/B.TECH(CS/IT),MCS,MCA.
  • Pass out Year: 2026 Only.
  • Percentage Criteria: NA.
  • Any Bond: No.
  • Certification(If Any): No.

Package Details:

  • Stipend during 6 Months of Internship period: Between Rs.10,000/- to Rs.20,000/- Per Month (Based on interview).
  • Approx. PPO after Internship period: Between Rs.3,00,000/- to Rs.5,00,000/- Per Annum (Based on the internship performance). 

Roles & Responsibilities:

  1. Assist in building, training, and testing machine learning models for real-world applications.
  2. Support data collection, cleaning, preprocessing, and transformation for model development.
  3. Experiment with ML algorithms and optimize models under supervision.
  4. Contribute to developing backend components that support AI/ML pipelines.
  5. Explore research papers and implement proof-of-concept (POC) solutions.
  6. Work on GenAI use cases such as RAG-based systems and vector database integrations.
  7. Collaborate with team members to design and deliver AI-driven solutions.
  8. Stay updated with emerging trends and technologies in AI, ML, and deep learning.
  9. Document experiments, model results, and technical learnings clearly.
  10. Participate in brainstorming and problem-solving discussions for AI solutions.

Skills Required:

  1. Strong proficiency in Python programming.
  2. Understanding of machine learning algorithms and data preprocessing techniques.
  3. Experience with ML libraries such as scikit-learn, TensorFlow, or PyTorch.
  4. Knowledge of SQL and data handling techniques.
  5. Familiarity with cloud platforms such as AWS, Azure, or GCP (preferred).
  6. Basic understanding of GenAI concepts like RAG, LangChain, and vector databases (preferred).
  7. Exposure to NLP or Computer Vision projects (academic or personal).
  8. Awareness of model training, evaluation, and deployment concepts.
  9. Understanding of problem-solving and analytical thinking for AI solutions.
  10. Strong communication, teamwork, and learning mindset.

Location