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AI Engineer / Machine Learning Engineer – MLOps

Role overview

Qualifications

  • 3-7 years in Machine Learning / AI / Data Engineering
  • 2+ years in MLOps / model deployment / ML pipelines
  • Experience deploying models to production
  • Proficiency with MLOps tools (e.g., MLflow, Kubeflow, Airflow, DVC)

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

About the company

KATBOTZ logo

KATBOTZ

Welcome to KATBOTZ: Empowering Business Transformation & Innovation Stay steps ahead of the competition with our cutting-edge business consulting services, expertly optimized for the latest technologies. Ignite growth and knowledge with our transformative education services, while securing top-tier talent for your organization through our unrivaled recruiting solutions. Business Consulting: We specialize in serving enterprise and mid-market customers in the life sciences, hi-tech, and consumer goods industries. Our core offerings include finance transformation, solution integration, data management, reporting and analytics, and program management. Additionally, we have strategic partnerships to support our clients in additional areas. Solutions: We are investing in cutting-edge solutions and technology innovations to bring rapid time-to-value for our customers. By leveraging automation, AI, and machine learning, we help address our clients' most pressing business challenges. Education: We share our expertise to empower the new workforce and business users with the latest knowledge in technology. Through our educational initiatives, we equip them with the skills and insights necessary for success in today's rapidly evolving business landscape. Talent: Finding top-tier talent can be challenging, but with our comprehensive recruiting solutions, you can trust that you'll access the best professionals in the industry. Furthermore, we offer coaching and mentoring services to support the growth and development of the new workforce. Our passion for making a real impact drives us to serve our customers with dedication and expertise. We differentiate ourselves by offering competitive prices, quality resources, and minimal overheads to provide our clients with the best value. Join us as we work to make business transformation a reality for our clients. Let's create a brighter future together. We value feedback, please submit here: https://forms.gle/vpj5qi3HxrQK1Aee6

Company details

Company typeSmall startup
Company size2 - 10

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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.



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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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