MLOps Engineer
FundamentalPredictive Analytics company
RemoteSenior
Oak HC/FT
Valor Equity Partners
Battery Ventures
Salesforce Ventures
Hetz Ventures
Data & AI
About the role
TL;DR
Develop and manage scalable ML pipelines and robust model serving infrastructure.
- •Join Fundamental, an AI company pioneering enterprise decision-making.
- •Develop and manage scalable ML pipelines and robust model serving infrastructure.
- •Key Responsibilities Develop and manage scalable, automated machine learning pipelines, CI/CD workflows, and orchestration frameworks Design and implement robust model serving infrastructure using platforms like TorchServe, TensorFlow, Triton etc.
- •Develop scalable inference architectures optimized, with ultra-low latency and high throughput Ensure seamless model deployment by implementing A/B testing, canary releases, and rollback capabilities Develop logging, alerting, and monitoring solutions to track model development, and reliability Requirements Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience) 5+ years of experience as MLOps engineer or DevOps roles, working with MLOps platforms (MLflow, WandB etc..) and frameworks (PyTorch, TensorFlow etc..) Experience building and designing MLOps infrastructure from the ground up
Required skills
PythonBashGoKubernetesAWSMLflowPyTorchTensorFlowTerraformHelmPrometheusGrafanaDatadog
Nice-to-have skills
MLflowKubeflowFastAPIDatabricksSnowflakePrometheusGrafanaDatadog
Domain expertise
ai
Benefits & perks
Competitive compensation with salary and equity, Comprehensive health coverage, Paid parental leave, Relocation support, Mission-driven culture
Tech stack
PythonBashGoKubernetesAWSMLflowPyTorchTensorFlowTerraformHelmPrometheusGrafanaDatadog
