Job Description – AI/ML Engineer Job Title: AI/ML Engineer
Experience: 1–2 Years
Location: Chennai
Employment Type: Full-Time
Job Summary
We are looking for a motivated AI/ML Engineer with 1–2 years of experience to join our technology team in Chennai. The ideal candidate should have strong programming skills in Python and hands-on experience in Generative AI. The candidate will work on developing, integrating, and deploying AI/ML solutions and contribute to real-world GenAI initiatives.
Key Responsibilities
- Develop and implement AI/ML solutions using Python.
- Work on Generative AI applications, including LLM-based solutions.
- Develop and integrate AI models and APIs into business applications.
- Work with LLMs, prompt engineering, embeddings, and vector databases.
- Build and test AI/ML models and evaluate their performance.
- Assist in developing RAG (Retrieval-Augmented Generation) based applications.
- Perform data preprocessing, feature engineering, model evaluation, and optimization.
- Collaborate with software engineers, data engineers, and business stakeholders to integrate AI solutions.
- Debug, test, and optimize AI/ML applications for performance and reliability. Stay updated with the latest developments in Generative AI, LLMs, and AI/ML technologies.
Mandatory Skills
- 1–2 years of professional experience in AI/ML Engineering or a related role.
- Strong hands-on programming experience in Python.
- Mandatory hands-on experience in Generative AI.
- Good understanding of Large Language Models (LLMs).
- Experience with Prompt Engineering. Understanding of RAG architecture and applications.
- Knowledge of AI/ML concepts, algorithms, and model evaluation.
- Experience working with REST APIs and integrating AI models into applications.
- Good problem-solving and analytical skills
Good to Have
- Experience with Open AI, Azure OpenAI, Gemini, Claude, or similar LLM platforms.
- Experience with LangChain or LlamaIndex. Knowledge of vector databases such as FAISS, Pinecone, Chroma, or Weaviate. Exposure to Hugging Face and open-source LLMs.
- Basic knowledge of Docker, Git, and cloud platforms such as AWS/Azure/GCP.
- Exposure to AI Agents, fine-tuning, embeddings, or MLOps.
