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.