7 Ray Serve Jobs

Role Overview: As a Senior Technical Architect specializing in Data Science & Agentic AI, you will play a crucial role in leading the end-to-end modeling lifecycle. Your main responsibilities will include problem framing, experiment design, production deployment, and monitoring. You will be tasked with setting up the technical architecture for ML/GenAI and agentic systems. While collaborating with DE/Platform teams, your primary focus will be on modeling excellence, MLOps, and AI solution architecture to impact business KPIs positively. Key Responsibilities: - Own the technical vision for data-science initiatives and translate ambiguous business goals into modellable problems, KPIs, and NFRs...

Role Overview: As part of the team, you will be responsible for designing and developing a modular, scalable AI platform to serve foundation models and RAG-based applications. Your role will involve building pipelines for embedding generation, document chunking, and indexing. Additionally, you will develop integrations with vector databases like Pinecone, Weaviate, Chroma, or FAISS, and orchestrate LLM flows using tools like LangChain, LlamaIndex, and OpenAI APIs. Implementing RAG architectures to combine generative models with structured and unstructured knowledge sources will also be a key part of your responsibilities. You will create robust APIs and developer tools for easy adoption of A...

Description Hungry, Humble, Honest, with Heart. The Opportunity The current global team members are skilled in domain modeling, database design, big data, Java, go lang, and messaging and monitoring, so this is an excellent opportunity to play a key role in a rapidly growing team. About The Team At Nutanix, you would be joining the Next Gen- Data Engineering team comprised of more than 40 skilled professionals. Our team thrives in an open culture with a flat hierarchy, where collaboration and innovation are at the heart of everything we do. You can expect to work alongside talented individuals who are passionate about pioneering new solutions in the tech industry. You will report to the Seni...

Roles and Responsibilities Design, test, and refine prompts to optimize LLM performance across diverse tasks and domains Build and maintain a library of prompt templates and reusable components Collaborate with engineers, analysts, and business teams to embed prompt engineering into broader AI workflows Analyse model outputs and user feedback to iteratively improve prompt accuracy, consistency, and relevance Monitor developments in the fields of prompt engineering, generative AI, and LLM capabilities to inform internal practices Contribute to documentation, internal guidelines, and knowledge-sharing initiatives related to prompt engineering Required Background Demonstrable experience with pr...

**Job Description:** As an SRE DevOps in the ML Ops role, you will be responsible for designing, building, refactoring, and releasing software primarily in Python. Your hands-on experience with ML frameworks such as PyTorch, TensorFlow, and Triton will be crucial in handling framework-related issues, version upgrades, and ensuring compatibility with data processing and model training environments. Experience with AI/ML model training and inferencing platforms will be advantageous, as well as familiarity with the LLM fine-tuning system. Your debugging and triaging skills will be put to the test, along with your knowledge of cloud technologies like Kubernetes, Docker, and Linux fundamentals. B...

Role Overview: You are a highly skilled Generative AI Solution Architect with expertise in Agentic AI frameworks and Small Language Models (SLMs). Your role involves designing, architecting, and deploying scalable AI-driven solutions in industrial contexts to enhance operations in various sectors such as manufacturing, oil & gas, transportation, energy, smart infrastructure, and related verticals. Key Responsibilities: - Lead the end-to-end design and deployment of generative AI systems using LLMs and SLMs, integrated with Agentic AI workflows for autonomous reasoning, planning, and execution in complex industrial environments. - Select and fine-tune Small Language Models for domain-specific...

As an AI Platform Engineer, you should have a minimum of 8 years of experience in the relevant field, with internships, prototypes, and personal projects not being considered. Proficiency in coding is essential, preferably in Python or Java. You should possess experience in DevOps Culture, including owning development and deployment processes end-to-end. Additionally, you should have hands-on experience in building or deploying solutions in the cloud, either using Cloud Native services like S3, Lambda, AWS Batch, and ECS, or Cloud Agnostic solutions such as Kubernetes services. Having experience in Continuous Integration and Continuous Deployment (CICD) is crucial, with familiarity in tools ...