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Machine Learning Engineer – LLMOps

0 years

0 Lacs

india

Posted:1 week ago| Platform: Linkedin logo

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Skills Required

learning delphi consulting onboarding data analytics ai drive deployment scaling monitoring training tuning inference azure devops leadership design model security compliance research automation dataset mlflow databricks containerization docker kubernetes evaluation drift management programming compensation certifications support

Work Mode

Remote

Job Type

Full Time

Job Description

Ready to embark on a journey where your growth is intertwined with our commitment to making a positive impact? Join the Delphi family - where Growth Meets Values.


Delphi Consulting Pvt. Ltd.


About the Role:

LLM Ops Lead/Architect

The ideal candidate will have strong hands-on expertise with MLOps frameworks, cloud-native architectures (Azure preferred), and modern DevOps practices, combined with leadership skills to align cross-functional stakeholders and establish best practices for LLM operations.


What you'll do:

  • Lead the design and implementation of

    LLM Ops infrastructure

    for training, fine-tuning, and large-scale inference.
  • Establish and enforce

    best practices

    for model deployment, monitoring, retraining, and continuous improvement.
  • Implement

    security, compliance, and responsible AI guardrails

    to ensure safe and ethical LLM usage.
  • Partner closely with

    data science, research, and product teams

    to streamline the LLM lifecycle.
  • Build and manage

    Ops automation pipelines

    for dataset updates, retraining, and model versioning.
  • Evaluate and implement tools for

    cost optimization

    and

    performance tuning

    in large-scale environments.
  • Provide

    technical leadership

    and mentor teams on LLMOps methodologies.


What you'll bring:

  • Strong expertise in

    LLM deployment, scaling, and monitoring

    .
  • Proficiency in

    MLOps frameworks

    (Kubeflow, MLflow, Databricks deployment patterns).
  • Hands-on with

    cloud-native architectures

    (Azure preferred).
  • Strong background in

    CI/CD pipelines, containerization (Docker, Kubernetes), and microservices

    .
  • Solid understanding of

    observability tools

    (Prometheus, Grafana, OpenTelemetry).
  • Deep knowledge of

    model evaluation, drift detection, prompt management, and AI safety guardrails

    .
  • Programming expertise in

    Python

    and

    Bash scripting

    .
  • Experience with

    vector databases

    and

    RAG pipelines

    .
  • Strong

    leadership and stakeholder communication

    skills.
  • Knowledge of

    LLM safety, bias mitigation, and regulatory compliance

    .


What We Offer:


competitive compensation package, performance-based incentives,

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