Job Summary:
We are seeking a highly skilled and hands-on AI Engineer with 3+ years of proven experience in building and deploying solutions using Generative AI and Large Language Models (LLMs). You will work on cutting-edge applications leveraging transformer-based architectures, fine-tuning, prompt engineering, and scalable AI deployments.

This role is ideal for engineers passionate about AI research and real-world productization of generative AI technologies.

Key Responsibilities:

- Design, develop, and deploy solutions using LLMs (e.g., GPT, LLaMA, Mistral, Claude, PaLM, etc.) for various NLP and content generation tasks.
- Work on fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) pipelines.
- Integrate LLMs into enterprise applications with APIs and orchestrate workflows using Python, LangChain, or similar frameworks.
- Optimize model performance, latency, and cost for production use.
- Collaborate with data scientists, MLOps engineers, and product managers to deliver scalable AI features.
- Conduct experiments, analyze results, and publish internal findings or contribute to whitepapers.
- Ensure ethical, secure, and responsible use of AI technologies in all implementations.





Required Skills & Experience:

- 3+ years of hands-on experience working with Generative AI, LLMs, and NLP technologies.
- Robust programming skills in Python and experience with libraries like Transformers (Hugging Face), LangChain, PyTorch, TensorFlow, etc.
- Proven track record of fine-tuning LLMs, developing embeddings, and working with vector databases (e.g., FAISS, Pinecone, Weaviate).
- Experience deploying models on cloud platforms (AWS, Azure, GCP) and using ML pipelines or MLOps tools.
- Solid understanding of deep learning, NLP architectures, tokenization, and evaluation metrics for generative models.
- Experience in API development and integration of LLMs into user-facing applications.

Preferred Qualifications:

- Masters or PhD in Computer Science, AI/ML, Data Science, or related field.
- Experience with OpenAI APIs, Anthropic, Cohere, or open-source LLMs (e.g., Mistral, Falcon, LLaMA 3).
- Understanding of RLHF (Reinforcement Learning from Human Feedback) and model alignment techniques.
- Contributions to open-source AI projects or publications in GenAI/LLM.

📌 AI Engineer (Pune)
🏢 Shashwath Solution
📍 Pune