Senior AI/ML MLOps Engineer
Core
Design, develop, deploy, and manage machine learning solutions throughout the ML lifecycle, operationalizing models at scale via automated pipelines and monitoring. (via careerplan.io/jobs/CYNET-SYSTEMS-Senior-AIML-MLOps-Engineer-senior-aiml-mlops-engineer-at-cynet-systems)
Role type
Senior hands-on IC MLOps engineer
Builds
Automated training and deployment pipelines, model versioning systems, experiment tracking, and CI/CD processes for scalable AI/ML solutions
Domain
Cloud infrastructure (AWS/Azure/GCP) + Machine Learning Operations
Deliverable
production ML models
Required skills
Python, SQL, machine learning (supervised/unsupervised), feature engineering, hyperparameter tuning, MLOps tools (MLflow, Kubeflow, Azure ML, SageMaker, Vertex AI), containerization (Docker, Kubernetes), CI/CD (Jenkins, GitHub Actions, Azure DevOps), cloud platforms (AWS, Azure, GCP), data engineering (ETL/ELT), data quality, large-scale data processing
Preferred skills
Generative AI, LLMs, RAG, NLP, LLMOps, Databricks, Spark, feature stores, model governance, explainability, responsible AI, Agile/Scrum
Technologies
AWS, Azure, GCP, Docker, Kubernetes, MLflow, Kubeflow, Jenkins, GitHub Actions, Azure DevOps, PyTorch, TensorFlow, XGBoost, Scikit-learn, Spark, Databricks, Evidently
Responsibilities
Design and build automated ML pipelines; manage model versioning, experiment tracking, and drift detection; collaborate with data scientists, engineers, and stakeholders to deliver reliable AI solutions
Seniority
Senior, hands-on IC
