Collaborate with partners/stakeholders to understand the requirements of our AI development teams and key challenges.
Design, build, and maintain cloud infrastructure on AWS and Azure to support AI/ML workloads.
Implement and manage containerization technologies (Docker) and orchestration platforms (Kubernetes).
Develop and maintain CI/CD pipelines for automating the deployment and management of AI infrastructure.
Develop and maintain monitoring and alerting systems to ensure the health and performance of production AI infrastructure.
Analyze system performance data to identify bottlenecks and opportunities for improvement.
Mentor and learn from your peers, foster continuous learning of new cloud technologies and best practices.
Get good at our team’s processes and best practices and apply them to given tasks with help from peers and your manager.
Make sure to understand the underlying problems you try to solve with these tasks, and your implementations effectively address these problems in a reliable and sustainable way.
Partner with team members in development and problem-solving.
Independently complete work and proactively seek reviews from senior engineers on your work to ensure high quality.
Perform technical discussions.
Proactively review work from peers and learn.

Requirements

Bachelor's degree in Computer Science, Software Engineering, or a related field; or demonstrable equivalent deep understanding, experience, and capability.
A Master's or PhD degree in Computer Science (or related field) is a plus.
2+ years of experience in software engineering or cloud infrastructure, with a focus on supporting AI/ML workloads.
Demonstrable strong programming skills in a 3GL strongly-typed language like Java, Python, C/C++ or Golang.
Strong understanding of cloud platforms (AWS and Azure), including services relevant to AI/ML (e.g., EC2, S3, EKS, Azure ML, AKS).
Hands-on experience with containerization (Docker) and container orchestration (Kubernetes).
Experience with building and managing CI/CD pipelines for infrastructure and ML model deployment (using tools like Jenkins, GitLab CI/CD, etc.).
Strong understanding of networking concepts (VPC, subnets, routing, firewalls) and experience configuring network infrastructure in the cloud.
Experience with infrastructure monitoring and alerting tools (e.g., Prometheus, Grafana, CloudWatch, Azure Monitor).
Strong scripting skills (Python, Bash) for automation and configuration management.
Excellent problem-solving skills, with the ability to analyze complex systems and identify performance bottlenecks.
Strong communication and collaboration skills, with the ability to work effectively in a team environment.

Benefits

health, dental and vision insurances
retirement savings plan
paid time off
health savings account
flexible spending accounts
life insurance
disability insurance
tuition reimbursement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

programming skillsJavaPythonC/C++Golangcloud infrastructureAI/ML workloadscontainerizationDockerKubernetes

Soft Skills

problem-solving skillscommunication skillscollaboration skillsmentoringcontinuous learningindependently complete workproactive reviewtechnical discussions

Certifications

Bachelor's degree in Computer ScienceMaster's degree in Computer SciencePhD in Computer Science