AI/ML Engineer

Develop and deploy AI/ML models using Python.Work with LLM-based solutions (prompt engineering, fine-tuning, embeddings, model evaluation).Build scalable ML pipelines for training, inference, and automation.Analyze datasets and develop algorithms to solve business problems.Integrate AI models into applications using APIs or microservices.Collaborate with cross-functional teams for feature development.Optimize model performance, accuracy, and latency.Required Skills Strong experience in Python and ML libraries (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow).Hands-on experience with LLMs (OpenAI, HuggingFace, LangChain, RAG, fine-tuning).Good understanding of Machine Learning and Deep Learning concepts.Experience with data processing, feature engineering, and NLP.Knowledge of cloud platforms (AWS/Azure/GCP) is a plus.Strong problem-solving and communication skills.Nice to Have Experience with vector databases (FAISS, Pinecone).Knowledge of MLOps tools (MLflow, Docker, Kubernetes).Experience with RAG pipelines and Generative AI apps.Role & responsibilities Develop and deploy AI/ML models using Python.Work with LLM-based solutions (prompt engineering, fine-tuning, embeddings, model evaluation).Build scalable ML pipelines for training, inference, and automation.Analyze datasets and develop algorithms to solve business problems.Integrate AI models into applications using APIs or microservices.Collaborate with cross-functional teams for feature development.Optimize model performance, accuracy, and latency.Required Skills Strong experience in Python and ML libraries (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow).Hands-on experience with LLMs (OpenAI, HuggingFace, LangChain, RAG, fine-tuning).Good understanding of Machine Learning and Deep Learning concepts.Experience with data processing, feature engineering, and NLP.Knowledge of cloud platforms (AWS/Azure/GCP) is a plus.Strong problem-solving and communication skills.Nice to Have Experience with vector databases (FAISS, Pinecone).Knowledge of MLOps tools (MLflow, Docker, Kubernetes).Experience with RAG pipelines and Generative AI apps.Role & responsibilities