Mature our Machine Learning Operations Platform and advocate best practices to MLops engineers and design and implement scalable, automated workflows for the complete ML lifecycle
Maintain Kubernetes-based infrastructure for model training, deployment, and monitoring
Develop solutions for workload orchestration and time-slicing using tools like Flyteand Ray
Implement and optimize CI/CD pipelines tailored for machine learning applications
Leverage GPU capabilities, including MIG, to maximize efficiency for AI/ML workloads
Set up model monitoring systems to track performance, ensure robustness, and scale workloads as needed
Collaborate with engineers to build and maintain robust, pipelines for training and inference workflows
Develop Infrastructure-as-Code (IaC) solutions for deploying and managing cloud/on-prem ML environments
Design and develop intuitive, user-friendly self-service portals using React to enable data scientists and engineers to manage ML pipelines, monitor models, and access resources seamlessly
Participate in 24x7 on-call rotation
What You’ll Bring
Strong hands-on experience with tools and frameworks like Kubernetes, Kubeflow, MLflow, Flyte, / Ray
Proven experience with React for building interactive web applications, especially self-service portals that enhance the user experience for managing ML pipelines and workflows
Expertise in MIG, time-slicing, and scaling AI workloads efficiently
Proficiency in Python, Golang and bash for pipeline development, and automation
Model Deployment and Serving: Tensorflow Serving, TorchServe, FastAPI, Flask,REST/gRPC on scalable architectures
Proficiency with Linux fundamentals and performance optimizations
Experience with configuration management software (Ansible, etc.), systems monitoring & alerting (Prometheus, Grafana, Telegraf, Splunk, etc.)
Strong analytical and problem-solving abilities to troubleshoot and optimize AI/ML systems
Ability to collaborate with cross-functional teams, including data scientists, data engineers, and DevOps engineers, to deliver high-quality solutions.Excellent troubleshooting skills in production
Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering, Physics or proof of exceptional skills in related field or equivalent experience