AI Engineer with Python_100% Remote

Job Title - AI Engineer with Python Experience Required - 6+ years Time zone - 2pm -10PM Work Mode - Remote Position overview We are seeking a skilled AI Engineer to design, develop, and deploy AI-ML driven solutions that enhance business capabilities, automate processes, and improve customer and employee experiences. The ideal candidate has a strong foundation in machine learning, large language models (LLMs), data engineering, and cloud platforms, with the ability to productionize models at scale. Responsibilities - Design, build, and deploy machine learning and generative AI models, including LLMs, embeddings, transformers, and RAG pipelines. - Develop scalable AI services and microservices using Python, REST APIs, and cloud native technologies. Optimize models for performance, accuracy, and cost efficiency. - Work with structured and unstructured datasets for feature engineering, vectorization, and model training. Build data pipelines for training, validation, and inference. - Collaborate with data engineering teams on data ingestion, storage, and governance. - Implement CI/CD pipelines for machine learning models and MLOps workflows. - Monitor model performance and drift, and implement retraining strategies. - Manage model lifecycle processes, logging, and observability. - Integrate AI systems with enterprise applications, APIs, and cloud platforms such as Azure, AWS, and GCP. - Build Retrieval Augmented Generation (RAG) architectures leveraging vector databases such as Pinecone, FAISS, Weaviate, or Azure AI Search. - Ensure solutions align with enterprise security, compliance, and responsible AI standards. - Work with product, engineering, domain experts, and business teams to translate requirements into technical solutions. - Communicate AI capabilities and limitations to non-technical stakeholders. - Conduct proofs of concept (POCs), demonstrations, and conceptual solution design activities. Requirements - Strong proficiency in Python, including NumPy, Pandas, PyTorch, TensorFlow, and Transformers minimum 5-6 years. - Hands-on experience with LLMs, including OpenAI, Azure OpenAI, Anthropic, and Llama models. - Experience with machine learning algorithms, natural language processing (NLP), deep learning, and vector embeddings. - Experience with cloud platforms such as Azure, AWS, and GCP, including serverless computing services. - Familiarity with MLOps tools such as MLflow, Kubeflow, Azure Machine Learning, Amazon SageMaker, or Databricks. - Experience working with vector databases, including Pinecone, Chroma, FAISS, and Azure AI Search. - Knowledge of containerization and orchestration technologies such as Docker and Kubernetes.