AI Engineer / Machine Learning Engineer – MLOps

KATBOTZ; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Professional development

Flexible remote work

Dynamic work environment

Job summary

KATBOTZ LLC is seeking an AI Engineer / Machine Learning Engineer with strong MLOps experience to design, deploy, monitor, and maintain ML models in production environments. This position is remote and offers opportunities to work across cloud platforms and scalable ML pipelines.

You will build ML pipelines, automate model deployment with CI/CD, manage the model lifecycle, and ensure reliability, governance, and data quality while collaborating with data scientists and AI developers.

Qualifications

• 3–7 years in Machine Learning / AI / Data Engineering
• 2+ years in MLOps / Model Deployment / ML Pipelines
• Experience deploying models to production is mandatory

Responsibilities

• Build and maintain ML pipelines for training, testing, and deployment
• Deploy ML models into production environments
• Manage model lifecycle (training, deployment, monitoring, retraining)
• Automate workflows using CI/CD for ML models
• Monitor model performance, drift, and data quality
• Work with data scientists and AI developers to productionize models
• Manage model versioning, data versioning, and experiment tracking
• Deploy models on cloud platforms (AWS, Azure, GCP)
• Containerize applications using Docker and Kubernetes
• Implement monitoring and logging for ML systems
• Ensure scalability, security, and reliability of AI systems

Skills

Python

Machine Learning

MLOps

Docker

Kubernetes

CI/CD

MLflow

Kubeflow

Airflow

DVC

Weights & Biases

SageMaker

Azure ML

Vertex AI

Terraform

Data pipelines

APIs

AWS

Azure

GCP

SQL

NoSQL

Model monitoring

Tools

Docker

Kubernetes

GitHub Actions

Jenkins

GitLab CI

Job description

This is a remote position. AI Engineer / Machine Learning Engineer – MLOps We are looking for an AI Engineer with strong experience in Machine Learning Operations (MLOps) to design, deploy, monitor, and maintain machine learning and AI models in production environments. The candidate will be responsible for building scalable ML pipelines, automating model deployment, managing model lifecycle, and ensuring reliability, performance, and governance of AI systems.

Key Responsibilities

• Build and maintain ML pipelines for training, testing, and deployment
• Deploy machine learning and AI models into production environments
• Manage model lifecycle (training, deployment, monitoring, retraining)
• Automate workflows using CI/CD for ML models
• Monitor model performance, drift, and data quality
• Work with data scientists and AI developers to productionize models
• Manage model versioning, data versioning, and experiment tracking
• Deploy models on cloud platforms (AWS, Azure, GCP)
• Containerize applications using Docker and Kubernetes
• Implement monitoring and logging for ML systems
• Ensure scalability, security, and reliability of AI systems

Requirements

Required Skills

• Python
• Machine Learning
• MLOps tools and frameworks
• Docker
• Kubernetes
• CI/CD (GitHub Actions, Jenkins, GitLab CI)
• MLflow / Kubeflow / Airflow
• Data pipelines
• APIs (FastAPI / Flask)
• Cloud platforms (AWS / Azure / GCP)
• SQL / NoSQL databases
• Model monitoring and logging

MLOps Tools (Important)

Candidate should have experience in some of these:

• MLflow
• Kubeflow
• Airflow
• DVC
• Weights & Biases
• SageMaker
• Azure ML
• Vertex AI
• Docker
• Kubernetes
• Terraform

Experience Required

• 3–7 years in Machine Learning / AI / Data Engineering
• 2+ years in MLOps / Model Deployment / ML Pipelines
• Experience deploying models to production is mandatory

Education Benefits

• Competitive compensation package
• Opportunities for professional development and career advancement.
• Flexible working conditions, with remote options available.
• Dynamic and supportive work environment.

Equal Employment Opportunity

KATBOTZ LLC is an Equal Opportunity Employer.

We provide equal employment opportunities to all qualified individuals, regardless of race, religion, gender, gender identity, age, marital status, national origin, sexual orientation, citizenship status, veteran status, disability, or any other legally protected status.

As an organization, we are unwavering in our commitment to maintaining a discrimination‑free work environment, and fostering a culture of inclusivity, belonging and equal opportunity for all employees and applicants.