AI/ML Engineer
We're seeking an experienced AI/ML Engineer to lead our generative AI initiatives, focusing on large language models and agentic AI. You'll design, build, and maintain end-to-end machine learning pipelines; design scalable, production-grade AI services that integrate with our internal tools, cloud platforms, and real-world data sources; and collaborate across teams to turn complex business challenges into robust, data-driven solutions.
Responsibilities:
Design and implement effective prompt engineering and context strategies. Develop AI agents, including multi-agent collaboration for complex tasks. Implement tool-calling mechanisms and structured output generation with LLMs. Perform comprehensive data preprocessing and transformation for LLM-based solutions Apply agentic orchestration concepts for workflow automation and task breakdown. Integrate LLMs with external tools, including web search, data scraping, and third-party APIs. Develop AI-driven automated testing strategies to validate models and workflows Perform model selection and evaluation based on use case, performance, and cost. Conduct cost analysis for training and inference workloads across environments. Fine-tune large language models for task-specific performance. Work with cloud platforms (e.g., Azure) to deploy scalable AI systems. Build and maintain end-to-end ML pipelines from data ingestion to model deployment Design systems for both on-premise and cloud-based AI applications
Requirements:
Minimum 4 5 years of experience in AI/ML engineering Strong Python programming skills Hands-on experience with libraries such as LangChain (or LangGraph), LlamaIndex, PyTorch, or similar Experience deploying and managing ML models in or On-Prem cloud environments. Solid understanding of ML system design, including security, scalability, and efficiency Understanding of LLM integrations, Context engineering, and agent-based frameworks Strong problem-solving skills and the ability to work on complex systems independently
Apply Now
Responsibilities:
Design and implement effective prompt engineering and context strategies. Develop AI agents, including multi-agent collaboration for complex tasks. Implement tool-calling mechanisms and structured output generation with LLMs. Perform comprehensive data preprocessing and transformation for LLM-based solutions Apply agentic orchestration concepts for workflow automation and task breakdown. Integrate LLMs with external tools, including web search, data scraping, and third-party APIs. Develop AI-driven automated testing strategies to validate models and workflows Perform model selection and evaluation based on use case, performance, and cost. Conduct cost analysis for training and inference workloads across environments. Fine-tune large language models for task-specific performance. Work with cloud platforms (e.g., Azure) to deploy scalable AI systems. Build and maintain end-to-end ML pipelines from data ingestion to model deployment Design systems for both on-premise and cloud-based AI applications
Requirements:
Minimum 4 5 years of experience in AI/ML engineering Strong Python programming skills Hands-on experience with libraries such as LangChain (or LangGraph), LlamaIndex, PyTorch, or similar Experience deploying and managing ML models in or On-Prem cloud environments. Solid understanding of ML system design, including security, scalability, and efficiency Understanding of LLM integrations, Context engineering, and agent-based frameworks Strong problem-solving skills and the ability to work on complex systems independently
Apply Now