Site Reliability Engineer, AI/ML Platforms

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Job Overview

The Site Reliability Engineer (SRE) for AI/ML Platforms at Adobe will play a critical role in ensuring the reliability, scalability, and performance of AI and machine learning services. This position requires a proactive engineer who can leverage their expertise to bridge the gap between development and operations. The SRE will be responsible for automating processes, managing infrastructure, monitoring system performance, and collaborating with cross-functional teams to support the delivery of innovative solutions that enhance Adobe's AI and ML offerings.

Job Responsibilities

• Develop and maintain robust monitoring and alerting systems to ensure the operational efficiency of AI/ML platforms.
• Automate repetitive tasks through scripting and tooling to enhance operational efficiency.
• Conduct root cause analysis of incidents and lead efforts to solve systemic issues.
• Collaborate with engineering teams to design, build, and implement scalable and highly available service architectures.
• Define Service Level Objectives (SLOs) and metrics for platforms to ensure optimal performance.
• Participate in on-call rotations and incident response for production systems.
• Advise and implement best practices in software development, operations, and cloud infrastructure management.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in Site Reliability Engineering, DevOps, or a similar role.
• Proficiency in programming languages such as Python, Go, or Java.
• Extensive experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and container orchestration (e.g., Kubernetes, Docker).
• Solid understanding of networking concepts, system internals, and distributed systems.
• Experience with configuration management tools (e.g., Ansible, Terraform).
• Familiarity with machine learning concepts and frameworks (e.g., TensorFlow, PyTorch) is a plus.

Technologies & Tools

The Site Reliability Engineer will work with an extensive range of technologies and tools including cloud services (AWS, Azure Google Cloud), container orchestration platforms (such as Kubernetes and Docker), monitoring and logging systems (like Prometheus, Grafana, and ELK stack), and automation tools (e.g., Terraform, Ansible). Additionally, familiarity with machine learning frameworks such as TensorFlow or PyTorch will be advantageous in helping to maintain and scale AI/ML systems.

Ideal Candidates

Ideal candidates for the Site Reliability Engineer role at Adobe will possess a strong analytical mindset and a passion for problem-solving. They should be self-motivated, team-oriented professionals who thrive in fast-paced environments. Excellent communication skills and the ability to work collaboratively across departments are essential. Candidates should demonstrate adaptability to evolving technologies and a consistent drive to improve processes and systems, ensuring the reliability and efficiency of AI/ML platforms.