MLOps Engineer

4 hours ago

Pune, India Peoplefy Full time

Position : MLOps : 7+ Type : Full-time


Job Summary :


We are seeking an experienced MLOps Engineer with 7+ years of professional experience in DevOps, MLOps, or infrastructure engineering. The ideal candidate will have at least 4 years of specialized experience in AI/ML environments.


This role is crucial for supporting our AI and ML initiatives, including GenAI platform development, deployment automation, and infrastructure optimization. You will be responsible for building robust, scalable, and automated pipelines that enable our data science and machine learning teams to deploy models efficiently and reliably.

Key Responsibilities :


- ML Platform Development : Contribute to the development and maintenance of our GenAI platform. You will design and implement the core infrastructure that enables the training, serving, and monitoring of machine learning models at scale.

- Deployment Automation : Build and manage automated deployment pipelines for machine learning models using tools like Jenkins or Harness. You will be responsible for establishing and enforcing CI/CD best practices in an ML environment.

- Infrastructure Management : Utilize your hands-on experience with cloud services to manage and optimize our infrastructure. You will leverage Kubernetes and Terraform to ensure our environments are scalable, reliable, and cost-effective.

- Scripting & Automation : Apply your strong experience in Python to develop automation scripts, tools, and workflows that streamline the entire MLOps lifecycle, from data ingestion to model deployment and monitoring.

- Collaboration : Work closely with data scientists, machine learning engineers, and other stakeholders to understand their needs and provide technical solutions that accelerate their work.

Required Skills & Qualifications :


- 7+ years of professional experience in DevOps, MLOps, or infrastructure engineering.

- 4+ years of specialized experience in AI/ML environments is highly preferred.

- Strong, hands-on experience with any cloud services (AWS, Azure, or GCP).

- Strong experience in Python.

- Proven experience with ML deployment using Jenkins or Harness.

- Hands-on experience with Kubernetes and Terraform.


(ref:hirist.tech)

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