AI/ML Engineer

Job Description: We are hiring an AI/ML Engineer to turn data into actionable insights through predictive models and automation. Strong understanding of machine learning algorithms and production-level deployment required. Required Skills & Qualifications: 5+ years of experience in AI/ML engineering, particularly within Azure Cloud and AI ecosystems. Strong hands-on expertise with OpenAI models, including knowledge of training, distillation, and model internals. Proficiency in Python, and experience with frameworks such as LangChain, FastAPI, or similar. Experience designing multi-threaded and concurrent systems optimized for performance and rate-limit constraints. Deep understanding of agent-based architectures, autonomous workflows, and orchestration techniques. Solid experience with PostgreSQL (PSQL) and SQL for building complex queries, performance tuning, and managing structured datasets. Familiarity with RAG, embedding-based retrieval, and vector databases. Understanding of LLM tokenization, rate limits, and optimization strategies for throughput and cost control. Responsibilities: Develop and deploy AI-driven applications leveraging Azure AI and OpenAI models. ⁠Design multi-threaded and parallel processing systems that operate efficiently within rate-limited API environments. ⁠Build intelligent agent-based AI architectures capable of dynamic reasoning and task automation. ⁠Integrate and manage PostgreSQL (PSQL) and other SQL-based systems for structured data access, transformation, and analysis. ⁠Perform data engineering tasks including data ingestion, transformation, and feature extraction for AI models. ⁠Optimize prompt workflows and token usage for LLM interaction, using tools like LangChain, FastAPI, and Azure OpenAI. ⁠Implement LLM-driven pipelines including RAG (retrieval-augmented generation), prompt chaining, and model evaluation. ⁠Collaborate with DevOps and cloud engineers to ensure secure, scalable, and efficient deployment of AI services on Azure. ⁠Contribute to improving model performance via prompt design, fine-tuning, or integration with external data sources. Show more Show less