Job description

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team. Role : MLOPS Engineer Location : Scottsdale AZ (Onsite) Contract : Long Term We are looking for a skilled MLOps Engineer to design, deploy, and manage scalable machine learning pipelines in production. The role focuses on enabling seamless integration of ML models into enterprise systems with reliability, automation, and governance . Key Responsibilities • Design and implement end-to-end ML pipelines from data ingestion to model deployment • Build and manage CI/CD pipelines for ML models (training, testing, deployment) • Automate model monitoring, retraining, and performance optimization • Collaborate with Data Scientists and Data Engineers for productionizing ML models • Ensure scalability, reliability, and security of ML systems • Manage model versioning, experiment tracking, and lifecycle management • Implement best practices for governance, compliance, and reproducibility Key Skills & Expertise • Strong programming skills in Python • Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn • Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow, SageMaker, Azure ML • Knowledge of CI/CD tools: Jenkins, GitHub Actions, GitLab CI • Experience with cloud platforms: AWS • Strong understanding of data pipelines, ETL processes, and distributed systems Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.

Requirements

Must-haves

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.
Role : MLOPS Engineer
Location : Scottsdale AZ (Onsite)
Contract : Long Term
Design and implement end-to-end ML pipelines from data ingestion to model deployment
Build and manage CI/CD pipelines for ML models (training, testing, deployment)
Automate model monitoring, retraining, and performance optimization
Collaborate with Data Scientists and Data Engineers for productionizing ML models
Ensure scalability, reliability, and security of ML systems
Manage model versioning, experiment tracking, and lifecycle management
Implement best practices for governance, compliance, and reproducibility
Key Skills & Expertise
Strong programming skills in Python
Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn
Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow, SageMaker, Azure ML
Knowledge of CI/CD tools: Jenkins, GitHub Actions, GitLab CI
Experience with cloud platforms: AWS
Strong understanding of data pipelines, ETL processes, and distributed systems

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlci/cdpythonazureaws

Platform: jobdiva
Effort: medium