Senior MLOps Software Engineer

Responsibilities

• Define scalable and secure architectures, frameworks and pipelines for building, deploying and diagnosing production ML applications
• Enable users & teams on the ML platform; troubleshoot and debug user issues; maintain user-friendly documentation and training
• Collaborate with internal stakeholders to build a comprehensive MLOps Platform
• Design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
• Develop standards and examples to accelerate the productivity of data science teams
• Run code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality, including data & concept drift
• Create ways to automate the testing, validation, and deployment of data science models
• Provide best practices and execute POCs for automated and efficient MLOps at scale

• Work with the core team; may work with additional teams when needed
• Internal only position
• Work with engineers and scrum teams

• Bachelor's degree with 5+ years experience
• Master’s degree with 3+ years experience

• 5+ years of experience working with an object-oriented programming language (Python, Golang, Java, C/C++ etc.)
• Experience with MLOps frameworks like MLflow, Kubeflow, etc.
• Proficiency in programming (Python, R, SQL)
• Ability to design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
• Strong understanding of Dev Ops principles and practices, CI/CD, etc. and tools (Git, Git Hub, jFrog Artifactory, Azure Dev Ops, etc.)
• Experience with containerization technologies like Docker and Kubernetes
• Strong communication and collaboration skills
• Ability to help work with a team to create User Stories and Tasks out of higher-level requirements

• Ability to create model inference systems with advanced deployment methods that integrate with other MLOps components like MLFlow
• Knowledge of inference systems like Seldon, Kubeflow, etc.
• Knowledge of deploying applications and systems in Langfuse or Kubernetes using Helm and Helmfile
• Knowledge of infrastructure orchestration using Cloud Formation or Terraform
• Exposure to observability tools (such as Evidently AI)

• Someone who takes the initiative on their own
• Someone who does not need to be micromanaged

Mid-Senior level

Contract

Information Technology

IT Services and IT Consulting