Women Re Launch- DevOps Engineer (women only)

Dailoqa; Varanasi; Presencial; INR 1 200 000 - 1 800 000; Tempo integral

Resumo da oferta

A leading AI firm in India is seeking a skilled DevOps Engineer to operationalize cutting-edge machine learning solutions. You'll work closely with data scientists and stakeholders to build MLOps pipelines ensuring efficient and secure deployment. The role demands deep experience with cloud services and container orchestration, along with a solid understanding of CI/CD practices. Strong leadership and cross-functional collaboration are essential. Join us in revolutionizing AI application deployment.

Qualificações

• Experience with cloud sourcing, VMs, and performance scaling.
• Strong experience with containerization and orchestration.
• Familiarity with CI/CD tools and infrastructure as code.

Responsabilidades

• Design and implement secure infrastructure for AI platforms.
• Automate CI/CD pipelines and model deployment workflows.
• Set up monitoring and alerting frameworks.

Conhecimentos

Cloud sourcing

Deep expertise in AWS, Azure, or GCP

Containerization and orchestration

CI/CD tools proficiency

Scripting languages proficiency

Knowledge of MLOps tools

DevOps principles application

Ferramentas

Terraform

Prometheus

Grafana

Docker

Kubernetes

GitHub Actions

MLflow

SageMaker

Descrição da oferta de emprego

Women join us as DevOps Engineer at Dailoqa, where you will be responsible for operationalizing cutting-edge machine learning and generative AI solutions, ensuring scalable, secure, and efficient deployment across infrastructure. You will work closely with data scientists, ML engineers, and business stakeholders to build and maintain robust MLOps pipelines, enabling rapid experimentation and reliable production implementation of AI models, including LLMs and real-time analytics systems.

To be successful as DevOps Engineer you should have experience with:

• Cloud sourcing, networks, VMs, performance, scaling, availability, storage, security, access management
• Deep expertise in one or more cloud platforms: AWS, Azure, GCP
• Strong experience in containerization and orchestration (Docker, Kubernetes, Helm)
• Familiarity with CI/CD tools: GitHub Actions, Jenkins, Azure DevOps, ArgoCD, etc.
• Proficiency in scripting languages (Python, Bash, PowerShell)
• Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML
• Strong understanding of DevOps principles applied to ML workflows.

Key Responsibilities may include:

• Design and implement scalable, cost-optimized, and secure infrastructure for AI-driven platforms.
• Implement infrastructure as code using tools like Terraform, ARM, or Cloud Formation.
• Automate infrastructure provisioning, CI/CD pipelines, and model deployment workflows.
• Ensure version control, repeatability, and compliance across all infrastructure components.
• Set up monitoring, logging, and alerting frameworks using tools like Prometheus, Grafana, ELK, or Azure Monitor.
• Optimize performance and resource utilization of AI workloads including GPU-based training/inference
• Experience with Snowflake, Databricks for collaborative ML development and scalable data processing.
• Understanding model interpretability, responsible AI, and governance.
• Contributions to open-source MLOps tools or communities.
• Strong leadership, communication, and cross-functional collaboration skills.
• Knowledge of data privacy, model governance, and regulatory compliance in AI systems.
• Exposure to LangChain, Vector DBs (e. g. , FAISS, Pinecone), and retrieval-augmented generation (RAG) pipelines.