Member of Technical Staff - 3 [AI/ML]

3 - 6 years

15 - 25 Lacs

Posted:1 week ago| Platform: Naukri logo

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Work Mode

Hybrid

Job Type

Full Time

Job Description

The Opportunity

Are you passionate about building intelligent, enterprise-grade AI systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic frameworks? At Nutanix, we're looking for a skilled and experienced AI/ML engineer to help shape the future of generative AI within our SaaS Engineering organization.

As a senior member of our team, youll work at the cutting edge of AI innovationdeveloping and deploying state-of-the-art LLMs and embedding models, optimizing model performance, and building scalable ML pipelines with real-world impact.


About the Team

At Nutanix, you will be joining a dynamic central platform team that plays a pivotal role in revolutionizing our approach to artificial intelligence and machine learning within the SaaS Engineering group. Comprising eight experienced engineers, our team specializes in addressing the GenAI, machine learning, and data science needs of various squads within the organization. Our diverse skill set ensures we collaborate effectively to create innovative solutions, leveraging the latest advancements in technology to drive our initiatives forward.

Your Role

  • Design and deploy

    Retrieval-Augmented Generation (RAG) pipelines

    .
  • Build, fine-tune, and deploy

    LLMs and embedding models

    such as

    LLaMA 3

    ,

    Gemma

    ,

    Mistral

    , and other domain-specific transformers.
  • Fine-tune both

    LLMs

    and

    embedding models

    for specialized enterprise tasks including Q&A, summarization, classification, and conversational AI.
  • Develop and maintain

    agentic frameworks

    capable of orchestrating task-specific intelligent agents with memory, planning, and tool-use capabilities.
  • Build and evaluate

    custom agents

    for use cases like document analysis, data querying, and interactive user support.
  • Implement

    evaluation frameworks

    for LLM outputs, including both automated metrics and task-specific success criteria.
  • Work closely with data engineering teams to develop

    custom training pipelines

    and extract meaningful insights from large-scale internal datasets.
  • Develop

    MLOps pipelines

    for training, deployment, and monitoring using tools like

    MLflow

    ,

    Kubeflow

    , and custom CI/CD workflows.
  • Deploy optimized

    inference endpoints

    for high-performance, low-latency model serving at scale.
  • Manage

    vectorization workflows

    using advanced embedding models and vector databases for semantic search and content retrieval.
  • Demonstrate working knowledge of LangChain, OpenAI function-calling, vector databases and scalable retrieval logic.
  • Work with Kubernetes clusters to provision, scale, and monitor AI/ML workloads; understand GPU, CPU, and storage hardware requirements for efficient deployment.
  • Collaborate with cross-functional teams including backend, data, and infrastructure engineers to integrate models seamlessly into production systems.

What You Will Bring

  • Bachelors, Masters, or Ph.D. in Computer Science, Machine Learning, Applied Math, or a related field.
  • 5+ years of hands-on experience building, deploying, and maintaining AI/ML systems in production environments.
  • Strong foundation in MLOps, including model versioning, CI/CD, monitoring, and retraining workflows.
  • In-depth understanding of Kubernetes (K8s) and GPU-based infrastructure, including container orchestration and GPU scheduling for AI workloads.
  • Experience working with Elasticsearch for semantic search and integrating it within RAG or LLM-driven architectures.
  • Proficient in Python (core ML libraries like PyTorch, Pandas, and NumPy).
  • Hands-on experience using Jupyter Notebooks for experimentation, documentation, and collaboration.
  • Comfortable with Unix-based systems, shell scripting, and command-line tooling for ML operations and debugging.
  • Familiarity with LangChain, LLM orchestration, and vector database integration.
  • Strong collaboration and communication skills, with the ability to mentor junior team members and drive initiatives independently.
  • Open-source contributions or published work in the ML/AI domain is a plus.

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Nutanix
Nutanix

Software Development

San Jose California

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