Note: The job is a remote job and is open to candidates in USA. CodeX Tech-IT LLC is a company focused on building intelligent solutions through advanced artificial intelligence. They are seeking a highly skilled AI Engineer to design, build, and deploy production-grade AI systems and machine learning pipelines.
Responsibilities
- System Architecture & Model Deployment
- Convert validated machine learning and deep learning prototypes into scalable, production-ready APIs and microservices
- Design and implement Retrieval-Augmented Generation (RAG) pipelines, semantic search, and agentic workflows using foundational LLMs
- Establish robust MLOps pipelines for automated model training, testing, continuous integration, and continuous deployment (CI/CD)
- Performance Optimization & Infrastructure
- Optimize AI models for latency, throughput, and compute efficiency (e.g., quantization, pruning, and caching strategies)
- Manage and scale vector databases (e.g., Pinecone, Milvus, Qdrant) and graph databases for efficient data retrieval
- Implement monitoring and logging frameworks to track model drift, data quality, and system performance post-deployment
- Cross-Functional Collaboration & Governance
- Partner with Data Engineering teams to establish clean, reliable data pipelines for model ingestion
- Work alongside Product Managers to translate business requirements into technical AI specifications
- Adhere to ethical AI guidelines, ensuring data privacy, security, and bias mitigation across all deployed models
Skills
- Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field
- Expert proficiency in Python
- Strong understanding of object-oriented programming, data structures, and algorithms
- Deep experience with PyTorch or TensorFlow, alongside Hugging Face Transformers, LangChain, or LlamaIndex
- Hands-on experience with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
- Proficiency in SQL and experience working with unstructured data platforms, NoSQL databases, and data orchestration tools (e.g., Apache Airflow)
- Experience with cloud-native AI platforms (e.g., AWS SageMaker, Google Vertex AI, Databricks)
- Familiarity with fine-tuning open-source LLMs (e.g., Llama, Mistral) and prompt engineering optimization
- Knowledge of distributed computing frameworks (e.g., Ray, Spark)
Company Overview