THE WORK: Explore new horizons with enthusiasm and curiosity. You will perform independently and become a subject matter expert while actively participating and contributing in team discussions. Your contributions will help provide thoughtful solutions to work-related challenges. This opportunity invites you to engage deeply with advanced Machine Learning, fostering growth and innovation. Join us in shaping the future with your expertise and passion.
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
________________________________________
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
________________________________________
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
________________________________________
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
________________________________________
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)
