๐ค Company: Aptino, Inc.
๐ Location: Viman Nagar, Pune
๐ข Work Mode: Work From Office
๐ Experience: 0โ1 Year
โก Joining: Immediate Joiners Preferred
๐ป Role: AI Engineer
๐ง Core Skills: Python | AI/ML | GenAI | Agentic AI | MLOps | LLMs | AI Frameworks
๐ฏ Eligible: Recent graduates from CS, AI/ML, Data Science or related fields
๐ฉ Apply: aditi.akulwar@aptino.com
๐ข About Aptino, Inc.
Aptino, Inc. is an IT services and consulting organization focused on technology solutions, talent development and workforce services. Aptino describes its work as combining AI technology and innovative methodologies with a client-centric approach. Its services include IT services, cloud transformation, data and analytics, intelligent automation, workforce management and learning & development.
Aptino has a Pune office in Viman Nagar, making this opportunity especially relevant for fresh graduates looking to begin their AI career through an office-based environment. The company also highlights continuous learning and career growth as part of its employee offering.
๐ Why This Role Is Good for Your Experience?
For a fresher, this opportunity can be an excellent starting point because the role is positioned around modern AI technologies rather than only traditional software development. ๐ค
You can potentially build experience across the AI lifecycleโfrom Python development and machine-learning fundamentals to LLM-based applications, Generative AI and emerging Agentic AI systems. This gives you a broader foundation for future roles such as AI Engineer, ML Engineer, GenAI Engineer, LLM Engineer, MLOps Engineer or AI Application Developer.
The combination of GenAI + Agentic AI + LLMs + MLOps is particularly valuable because modern AI engineering increasingly requires more than model knowledge. Engineers need to understand how models are integrated into applications, monitored, evaluated and eventually deployed. ๐
๐ง Skills Required
๐ Python: Strong programming fundamentals, OOP, functions, collections, exception handling and libraries such as NumPy/Pandas.
๐ค Machine Learning: Supervised/unsupervised learning, regression, classification, clustering, model evaluation and overfitting.
โจ Generative AI: LLM concepts, prompt engineering, embeddings, context handling and AI application development.
๐งฉ Agentic AI: Understanding agents, tools, workflows, planning, memory and multi-step AI tasks.
๐ง LLMs: Tokens, context windows, embeddings, inference, hallucinations and model limitations.
โ๏ธ MLOps: Model lifecycle, experiment tracking, deployment, monitoring, versioning and reproducibility.
๐ AI Frameworks: Familiarity with frameworks such as LangChain, LlamaIndex, Hugging Face or similar technologies is advantageous.
๐ Data Skills: SQL basics, data cleaning, preprocessing and visualization.
๐ APIs: REST APIs, JSON and integrating AI models into applications.
๐ฏ Preparation Tips
๐น 1. Make Python your strongest language: Practice coding questions involving strings, lists, dictionaries, arrays, functions, OOP and basic algorithms. As a fresher, strong Python fundamentals can make a major difference.
๐น 2. Build one complete GenAI project: Don’t rely only on certificates. Create a practical project such as a document Q&A chatbot, resume analyzer, AI research assistant or RAG application. Explain the architecture clearly. ๐
๐น 3. Learn RAG fundamentals: Understand document loading, chunking, embeddings, vector databases, retrieval and response generation. Even if RAG is not explicitly mentioned in the fresher JD, it is highly relevant to modern LLM engineering.
๐น 4. Understand Agentic AI: Be able to explain the difference between a normal chatbot and an AI agent. Learn how agents use tools, APIs and multi-step workflows to complete tasks.
๐น 5. Revise ML algorithms: Prepare linear/logistic regression, decision trees, random forests, clustering, feature engineering, train/test split, cross-validation and metrics such as precision, recall and F1-score.
๐น 6. Learn basic MLOps: Understand Git, environments, model versioning, experiment tracking, Docker basics, deployment concepts and monitoring. โ๏ธ
๐น 7. Prepare for practical scenarios: Recent public Aptino AI/ML interview feedback mentions an assessment/task followed by questions around edge cases, scenarios and machine-learning algorithms.
๐น 8. Know every project on your resume: Be prepared to explain your dataset, model choice, architecture, challenges, results and your exact contribution.
๐ค Expected Interview Rounds at Aptino
๐น Round 1 โ HR/Initial Screening: Education, projects/internships, communication, availability and interest in AI.
๐น Round 2 โ Technical/AI Interview: Python, ML fundamentals, AI concepts, algorithms and project discussion.
๐น Round 3 โ Assessment/Practical Task: A coding, ML or AI-related task may be used to evaluate practical problem-solving. This is especially important because recent Aptino AI/ML interview feedback specifically mentions an assessment/task.
๐น Round 4 โ Final Discussion: Depending on the hiring team, this may cover project fit, learning ability, communication and joining availability.
โ ๏ธ Note: The exact number and sequence of rounds can change depending on the hiring team and client/project requirements.
๐ฐ Salary Range
Aptino has not publicly specified the salary for this exact AI Engineer โ Fresher vacancy. Therefore, there is no reliable official company-specific salary figure to quote.
For market context, current Pune data places AI/ML Engineer base pay around โน5โ10.1 LPA, with an average around โน8 LPA across experience levels; fresher/0โ1 year compensation is generally lower than the overall market average.
๐ฐ Estimated fresher range for this opportunity: approximately โน3.5โ6 LPA, depending on academic background, AI/ML projects, internship experience, Python ability, GenAI knowledge and interview performance. This is a market estimate, not an official Aptino salary range.
๐ Resume Tips
๐ฏ Use a headline such as โAI/ML Engineer | Python | GenAI | LLM | Machine Learningโ instead of simply โFresher.โ
๐ Put Python prominently in your technical skills.
๐ค Create a dedicated AI/GenAI Projects section near the top of the resume.
๐ง Mention specific LLMs, AI frameworks and tools you have actually used.
๐ For every AI project, include problem โ technology โ implementation โ result.
โ๏ธ Mention MLOps exposure such as Git, Docker, MLflow, cloud deployment or CI/CD if genuinely used.
๐ Include relevant coursework such as Machine Learning, Deep Learning, NLP, Generative AI and Data Science.
๐ Internships should clearly explain your contribution rather than only stating the company name and duration.
๐ซ Avoid filling the resume with dozens of AI keywords without project evidenceโbe prepared to explain every technology during the interview.
๐ฉ How to Apply?
๐ง aditi.akulwar@aptino.com
Interested candidates can share their updated resume at:
๐ง aditi.akulwar@aptino.com
๐ Subject: Application โ AI Engineer โ Fresher | Pune
Before applying, make sure your CV clearly highlights Python + AI/ML + GenAI/LLM projects, along with internships or academic projects relevant to the role.
๐ฏ Who Should Apply?
๐ 2025/2026 graduates or recent graduates from Computer Science, Artificial Intelligence, Machine Learning, Data Science or related disciplines.
๐ป Candidates with strong Python fundamentals.
๐ค Candidates who have built AI/ML or GenAI projects.
๐ Candidates who enjoy learning emerging AI technologies.
โก Immediate joiners are preferred.
๐ Final Takeaway
This Aptino opening is a strong opportunity for fresh graduates who want to enter AI engineering directly rather than starting exclusively in conventional software development. The combination of Python, AI/ML, GenAI, Agentic AI, LLMs, AI frameworks and MLOps gives candidates a roadmap toward modern AI engineering careers. ๐ค๐
