3 Llmcompiler Jobs

Dreaming big is in our DNA. It's who we are as a company. It's our culture. It's our heritage. And more than ever, it's our future. A future where we're always looking forward. Always serving up new ways to meet life's moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources, and opportunities to unleash their full potential. The power we create together when we combine your strengths with ours is unstoppable. Are you ready to join a team that dreams as big as you do AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big We Need You. **Job Title:** Junior Data Scientist **Location:** Bangalore **Reporting to:** Senior Manager - Analytics **Purpose of the role:** The Global GenAI Team at Anheuser-Busch InBev (AB InBev) is tasked with constructing competitive solutions utilizing GenAI techniques. These solutions aim to extract contextual insights and meaningful information from our enterprise data assets. The derived data-driven insights play a pivotal role in empowering our business users to make well-informed decisions regarding their respective products. In the role of a Machine Learning Engineer (MLE), you will operate at the intersection of LLM-based frameworks, tools, and technologies, cloud-native technologies and solutions, and microservices-based software architecture and design patterns. As an additional responsibility, you will be involved in the complete development cycle of new product features, encompassing tasks such as the development and deployment of new models integrated into production systems. Furthermore, you will have the opportunity to critically assess and influence the product engineering, design, architecture, and technology stack across multiple products, extending beyond your immediate focus. **Key tasks & accountabilities:** **Large Language Models (LLM):** - Experience with LangChain, LangGraph - Proficiency in building agentic patterns like ReAct, ReWoo, LLMCompiler **Multi-modal Retrieval-Augmented Generation (RAG):** - Expertise in multi-modal AI systems (text, images, audio, video) - Designing and optimizing chunking strategies and clustering for large data processing **Streaming & Real-time Processing:** - Experience in audio/video streaming and real-time data pipelines - Low-latency inference and deployment architectures **NL2SQL:** - Natural language-driven SQL generation for databases - Experience with natural language interfaces to databases and query optimization **API Development:** - Building scalable APIs with FastAPI for AI model serving **Containerization & Orchestration:** - Proficient with Docker for containerized AI services - Experience with orchestration tools for deploying and managing services **Data Processing & Pipelines:** - Experience with chunking strategies for efficient document processing - Building data pipelines to handle large-scale data for AI model training and inference **AI Frameworks & Tools:** - Experience with AI/ML frameworks like TensorFlow, PyTorch - Proficiency in LangChain, LangGraph, and other LLM-related technologies **Prompt Engineering:** - Expertise in advanced prompting techniques like Chain of Thought (CoT) prompting, LLM Judge, and self-reflection prompting - Experience with prompt compression and optimization using tools like LLMLingua, AdaFlow, TextGrad, and DSPy - Strong understanding of context window management and optimizing prompts for performance and efficiency **Qualifications, Experience, Skills:** **Level of educational attainment required (1 or more of the following):** - Bachelor's or master's degree in Computer Science, Engineering, or a related field. **Previous Work Experience Required:** - Proven experience of 1+ years in developing and deploying applications utilizing Azure OpenAI and Redis as a vector database. **Technical Skills Required:** - Solid understanding of language model technologies, including LangChain, OpenAI Python SDK, LammaIndex, OLamma, etc. - Proficiency in implementing and optimizing machine learning models for natural language processing. - Experience with observability tools such as mlflow, langsmith, langfuse, weight and bias, etc. - Strong programming skills in languages such as Python and proficiency in relevant frameworks. - Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). And above all of this, an undying love for beer! We dream big to create a future with more cheer.,

Location : Bengaluru Employnment : Contractual Key Skills Large Language Models (LLM): Experience with LangChain, LangGraph Proficiency in building agentic patterns like ReAct, ReWoo, LLMCompiler Multi-modal Retrieval-Augmented Generation (RAG): Expertise in multi-modal AI systems (text, images, audio, video) Designing and optimizing chunking strategies and clustering for large data processing Streaming & Real-time Processing: Experience in audio/video streaming and real-time data pipelines Low-latency inference and deployment architectures NL2SQL: Natural language-driven SQL generation for databases Experience with natural language interfaces to databases and query optimization API Development: B uilding scalable APIs with FastAPI for AI model serving Containerization & Orchestration: Proficient with Docker for containerized AI services Experience with orchestration tools for deploying and managing services Data Processing & Pipelines: Experience with chunking strategies for efficient document processing Building data pipelines to handle large-scale data for AI model training and inference AI Frameworks & Tools: Experience with AI/ML frameworks like TensorFlow, PyTorch Proficiency in LangChain, LangGraph, and other LLM-related technologies Prompt Engineering: Expertise in advanced prompting techniques like Chain of Thought (CoT) prompting, LLM Judge, and self-reflection prompting Experience with prompt compression and optimization using tools like LLMLingua, AdaFlow, TextGrad, and DSPy Strong understanding of context window management and optimizing prompts for performance and efficiency

Location: Remote / Pan India , Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote Notice Period: Immediate iSource Services is hiring for one of their client for the position of AI/ML Engineer. About the Role - We are looking for a highly skilled ML Engineer with experience in cutting-edge design patterns and AI-powered applications. The ideal candidate will have a deep understanding of agentic design patterns, multi-modal RAG Systems, and practical product development experience. Design and implement Agentic Design Patterns, such as ReAct and ReWoo, to enhance the functionality and adaptability of AI systems. Utilize LLMCompiler to create efficient and scalable models and leverage LLM as Judge for decision making processes. Develop and optimize Multi-modal RAG systems, integrating diverse data modalities for advanced retrieval-augmented generation. Implement and maintain GraphRAG solutions for enhanced reasoning and contextual information retrieval. Collaborate with cross-functional teams to translate cutting-edge AI research into production-ready solutions. Contribute to the development of scalable and robust AI-powered products. Requirements: Strong knowledge of Agentic Design Patterns (ReAct, ReWoo). Proficiency in LLMCompiler and LLM as Judge methodologies. Experience building Multi-modal RAG and GraphRAG systems. 5+ years of experience in AI/ML development, including practical product development experience. Expertise in Python, machine learning frameworks (e.g., TensorFlow, PyTorch), and large language models (LLMs). Strong problem-solving and analytical skills with a focus on innovation. Preferred Skills: Familiarity with distributed systems and cloud platforms. Experience in data engineering and model optimization. Knowledge of graph databases and advanced information retrieval techniques. ML/AI development, Python Agentic Design Patterns (ReAct, ReWoo). LLMCompiler, LLM as judge. ML models, ML frameworks.