THE WORK: Explore the fascinating world of Large Language Models and immerse yourself in a role where your independent contributions will shape innovative solutions. You will actively participate in discussions and collaborate to provide thoughtful answers to complex challenges. This opportunity invites you to grow as a subject matter expert while engaging with cutting-edge technology. Join us in this exciting journey and make a meaningful impact.
Responsibilities:
Design and develop AI/ML and Generative AI solutions using Python
Build and deploy applications leveraging Large Language Models (LLMs)
Develop end-to-end pipelines including data ingestion, preprocessing, model integration, and deployment
Implement prompt engineering and fine-tuning strategies for LLMs
Integrate AI services into web/mobile/backend applications via APIs
Work with vector databases and embeddings for semantic search and RAG architectures
Optimize models and pipelines for performance, latency, and cost
Collaborate with cross-functional teams to translate business requirements into AI solutions
Ensure responsible AI practices including data privacy, bias mitigation, and explainability
Monitor and improve model performance in production environments
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Required Skills & Qualifications
6-8 years of experience in software engineering / AI / ML, Python roles,
Strong programming expertise in Python
Hands-on experience with ML/DL frameworks like PyTorch or TensorFlow
Experience with LLM frameworks such as LangChain or LlamaIndex
Solid understanding of NLP concepts and transformer-based models
Experience with REST APIs and microservices architecture
Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate)
Experience with version control systems like Git
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Preferred Qualifications
Experience working with APIs from providers like OpenAI or open-source LLMs (Llama, Mistral)
Knowledge of Retrieval-Augmented Generation (RAG) architectures
Experience with model fine-tuning and evaluation techniques
Exposure to cloud platforms (AWS / GCP) for deployment (excluding Azure)
Understanding of containerization tools like Docker
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Soft Skills
Strong analytical and problem-solving skills
Ability to translate complex AI concepts into practical solutions
Good communication and stakeholder management skills
Ability to work independently and in collaborative environments
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Nice to Have
Experience with AI agents / autonomous workflows
Knowledge of MLOps practices and CI/CD for ML pipelines
Exposure to multimodal AI (text, image, audio models)
Experience with real-time AI applications (chatbots, voice bots, copilots)
