MLOps Consultant

March 20

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Scopic

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Scopic is a software development company specializing in custom software solutions, mobile and web development, AI consulting, and digital marketing services. With expertise in various technologies such as PHP, Node. js, and AWS, Scopic caters to diverse industries including healthcare, finance, and education. They focus on transforming client ideas into innovative applications while ensuring high-quality user experiences and effective marketing strategies.

Scientific & Medical Visualization • CAD/CAM/CNC • Audio/Video Processing & Analytics • 3D Animation • Finance/Trading

201 - 500 employees

Founded 2006

📋 Description

• This is a remote position. • Design and implement automated, scalable, and reproducible MLOps pipelines. • Collaborate with data scientists, machine learning engineers, and DevOps teams to align ML models with production systems. • Develop and deploy CI/CD pipelines specifically tailored for machine learning models and AI agents. • Design infrastructure to support AI agent workflows, including data ingestion, model orchestration, and multi-agent systems. • Establish robust monitoring, logging, and alerting mechanisms for deployed models. • Guide and train the DevOps team on MLOps frameworks, best practices, and tooling. • Introduce and manage version control for data, models, and pipelines. • Ensure compliance with security and governance requirements throughout the AI/ML lifecycle. • Document processes and workflows to support knowledge transfer and long-term sustainability.

🎯 Requirements

• 2+ years of proven experience in MLOps, including model deployment, monitoring, and automation. • Strong background in DevOps practices and tools (e.g., Docker, Kubernetes, Terraform, CI/CD). • Knowledge of CI/CD tools like Jenkins, GitLab CI/CD. • Proficiency in machine learning lifecycle management tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). • Solid programming skills in Python and familiarity with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). • Experience with the main cloud platforms, particularly with AWS. • Familiarity with data pipeline tools and frameworks, such as Apache Airflow or Kubeflow. • Excellent communication skills to effectively mentor and collaborate with technical teams. • Ability to assess, architect, and implement MLOps solutions tailored to business needs.

🏖️ Benefits

• Paid training and professional opportunities. • Annual pay increases for good performance. • Flexibility to choose schedule and work location.