ML Infrastructure Engineer

ML Infrastructure Engineer

This role is a member of the AI/ML Infrastructure Engineering team and will be dedicated to implementing and supporting AI/ML infrastructure solutions in cloud and on-premise environments. The role will work directly with infrastructure teams and potentially face off with data scientists, machine learning engineers, application developers, and quantitative analysts by functioning as both a solutions architect and a professional services engineer.

This is a hands-on developer role, and candidates ideally have had experience deploying and supporting their own production-ready AI/ML models in cloud environments as well as automating the build and management of a broad range of cloud infrastructure using tools like Terraform. Candidates should be familiar with developing unit and functional tests, have experience designing and implementing CI/CD tools with infrastructure as code pipelines, and have knowledge of Linux systems administration, containerization, networking, security, automated configuration and state management, cross-system orchestration, configuration management, logging, metrics, monitoring, and alerting.

Principal Responsibilities:

1. Architect, develop and maintain internal AI/ML infrastructure components, frameworks, and offerings
2. Architect, develop and maintain AI/ML solutions for customers in cloud environments
3. Help customers architect, develop and maintain their own AI/ML solutions in cloud environments
4. Implement CI/CD pipelines which include application tests, security tests, and gates
5. Implement availability, security, performance monitoring, and alerting of AI/ML solutions
6. Automate data resiliency and replication for AI/ML models
7. Manage multiple environments and promote code between them
8. Automate systems configuration and orchestration using tools such as Terraform, Chef, Ansible, or Salt
9. Automate creation of machine images and containers

Required Qualifications/Skills:

1. 6+ years of experience designing and supporting production cloud environments
2. Experience consulting with customers to develop AI/ML solutions
3. Experience developing collaboratively, including infrastructure as code, preferably in Python
4. Systems engineering knowledge, including understanding of Linux, security, and networking
5. Cloud templating tools such as Terraform
6. Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch)
7. Experience with distributed computing tools (e.g., Ray, Dask)
8. Experience with model serving tools (e.g., vLLM, KFServing)
9. Experience with building, monitoring, and alerting on logs and metrics
10. Cloud Networking including connectivity, routing, DNS, VPCs, proxies, and load balancers
11. Cloud Security including IAM, Certificate Management, and Key Management
12. Excellent written and verbal communication skills
13. Excellent troubleshooting and analytical skills
14. Self-starter able to execute independently, on a deadline, and under pressure

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