2 - 5 years

4 - 7 Lacs

Posted:16 hours ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Role Overview

We are seeking a

Software Engineer with MLOps skills

to contribute to the deployment, automation, and monitoring of

GenAI and LLM-based applications

. You will work closely with AI researchers, data engineers, and DevOps teams to ensure seamless integration, scalability, and reliability of AI systems in production.

Key Responsibilities

1. Deployment & Integration

  • Assist in deploying and optimizing

    GenAI/LLM models

    on cloud platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
  • Integrate AI models with APIs, microservices, and enterprise applications for real-time use cases.

2. MLOps Pipeline Development

  • Contribute to building

    CI/CD pipelines

    for automated model training, evaluation, and deployment using tools like MLflow, Kubeflow, or TFX.
  • Implement model versioning, A/B testing, and rollback strategies.

3. Automation & Monitoring

  • Help automate model retraining, drift detection, and pipeline orchestration (Airflow, Prefect).
  • Assist in designing monitoring dashboards for model performance, data quality, and system health (Prometheus, Grafana).

4. Data Engineering Collaboration

  • Work with data engineers to preprocess and transform unstructured data (text, images) for LLM training/fine-tuning.
  • Support the maintenance of efficient data storage and retrieval systems (vector databases like Pinecone, Milvus).

5. Security & Compliance

  • Follow security best practices for MLOps workflows (model encryption, access controls).
  • Ensure compliance with data privacy regulations (GDPR, CCPA) and ethical AI standards.

6. Collaboration & Best Practices

  • Collaborate with cross-functional teams (AI researchers, DevOps, product) to align technical roadmaps.
  • Document MLOps processes and contribute to reusable templates.

Technical Skills

  • Languages:

    Proficiency in

    Python

    and familiarity with SQL/Bash.
  • ML Frameworks:

    Basic knowledge of

    PyTorch/TensorFl

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