Fundamental - MLOps Engineer
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 • Experience with model serving frameworks (TorchServe, TensorFlow Serving, Triton, KServe etc..) for high scalability and low latency inference • Experience in building and managing data pipelines to support both model training and inference • Experience with Kubernetes on a major cloud provider (AWS, GCP, or Azure) and with infrastructure as code (e.g. Terraform, Helm, GitOps) • Strong software engineering skills in Python, Bash, and Go, with a focus on writing clean, maintainable, and scalable code • Experience in AI/ML systems security, compliance, and model governance • Proficient with observability and monitoring tools, such as Prometheus, Grafana, Datadog, and OpenTelemetry • Experience with ML workflow tooling (MLflow, Kubeflow, or similar) • Experience with FastAPI and Backend applications • Familiarity with data platforms like Databricks or Snowflake • Exposure to SRE practices or cloud security certifications • Hands-on experience with Prometheus, Grafana, or Datadog
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 • Improve GPU usage, enable autoscaling, and streamline resource allocation to boost efficiency • Design, implement, and maintain feature stores, robust data pipelines, and scalable storage solutions to efficiently handle large volumes of data
Benefits
• Competitive compensation with salary and equity • Comprehensive health coverage for you and your dependents • Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys • Relocation support for employees moving to join the team in one of our office locations • A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
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