MLOPS (Freelance Via Shakers)

We are looking for a Machine Learning Engineer with strong expertise in MLOps to join our team. This role focuses on developing and maintaining automated ML systems, from training pipelines to inference services deployment. The ideal candidate will have a solid understanding of CI/CD workflows, cloud environments, and modern ML tools.

Responsibilities:

Design, develop, and maintain MLOps systems to automate ML workflows

Create and optimize training pipelines for machine learning models

Implement and manage inference services for production environments

Collaborate with data scientists and software engineers to integrate ML solutions

Ensure best practices in ML model versioning, monitoring, and deployment

Requirements:

Proficiency in Python and familiarity with Data Science frameworks

Strong understanding of CI/CD principles and experience with Kubernetes

Familiarity with cloud platforms, particularly AWS

Experience with MLOps tools such as Kubeflow Pipelines, MLflow, and FastAPIKnowledge of big data processing frameworks like Apache Spark

Solid grasp of software engineering principles and best practices

Excellent problem-solving skills and ability to work in a collaborative environment

Preferred Qualifications:

Experience with containerization technologies and microservices architecture

Familiarity with data versioning and experiment tracking in ML projects

Knowledge of model serving technologies and scalable inference systems

We're looking for a candidate who can bridge the gap between machine learning development and production deployment, ensuring our ML systems are scalable, maintainable, and efficient."