Job Description
📋 Description Lead the development and evolution of MLOps platforms, workflows, and infrastructure supporting Design and standardize processes for model development, training, deployment, monitoring, and Partner with data scientists and engineers to improve ML workflows from experimentation through Establish and maintain model governance practices, including reproducibility, lineage tracking Support ML tooling such as experiment tracking, model packaging, deployment workflows, and model Collaborate with multiple teams to onboard new ML use cases and improve shared ML capabilities. 🎯 Requirements 5+ years of experience in MLOps, machine learning engineering, platform engineering, data Strong hands-on experience managing production workloads in AWS and understanding of cloud Solid knowledge of the machine learning lifecycle, including model training, deployment Experience supporting production-grade ML workflows focused on reliability, scalability, and Familiarity with ML tooling such as MLflow, experiment tracking systems, model management Experience with workflow orchestration, infrastructure-as-code, and CI/CD practices for ML or data 🎁 Benefits Competitive salary and equity packages. Salary ranges based on location: Region 1: $172,550 – $203,000 Region 2: $158,950 – $187,000 Region 3: $147,900 – $174,000 Comprehensive health, dental, and vision insurance.
