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At Everseen, we are scaling the ML Platform powering our global machine learning lifecycle. Partnering closely with AI Engineering, Research, and Operations, we collaborate to accelerate engineering iteration, guarantee experiment reproducibility, and bring clear transparency to workloads, resource allocation, and cloud costs. In this role, you will help shape scalable services at the intersection of infrastructure and AI, contributing to a core sub-system or a significant slice of our MLOps platform.
Job Responsibility
Owns a core sub-system, a significant slice of a technology pillar, or complex business-critical features
Leads the design of complex features, services, or new sub-systems
Directly drives progress on highly complex tasks that involve multiple cross-functional dependencies, high business impact, or ambiguous requirements
Influences team-level architecture, implementation approaches, and continuous technical improvements
Contributes significantly to strategic technical decisions within your specific product, platform, or service area
Aligns technical consensus across team members and represents your team's sub-system in cross-pillar/cross-team discussions
Contributes hands-on to the most technically challenging parts of the team's workload
Designs and implements highly reusable, efficient, and elegant code
Improves team-level software quality by establishing stronger test coverage, advanced validation patterns, and proactive defect prevention
Drives improvements in team CI/CD processes and release quality through automated build, test, and deployment practices
Leads the diagnosis and troubleshooting of complex production issues within team systems
Utilizes production diagnostics, logs, stack traces, and system metrics to identify trends, isolate root causes, and propose engineering improvement opportunities
Research, evaluate, and propose third-party software solutions to optimize system performance and expand capabilities
Responsible for creating, reviewing, and maintaining high-quality technical documentation
Mentors engineers (SDE I/II) support their technical growth and reviews peers' designs
Proactively shares skills, knowledge, and technical expertise with members of the engineering team
Requirements
6+ years of relevant software engineering experience (or 3+ years of highly accelerated experience in a specialized global SaaS or high-growth technology environment)
Bachelor's degree in computer science, Engineering, or a related technical field (or equivalent practical experience)
In-depth knowledge of at least one relevant language (e.g., Python, JavaScript/TypeScript, C++)
Strong understanding of distributed systems, microservices, and modern software engineering architectures
Excellent troubleshooting skills within Linux environments
Strong understanding of major cloud platforms, including container orchestration, storage services, and cloud security and scalability principles
Excellent understanding of cloud computing service models, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) architecture
Solid understanding of engineering best practices, CI/CD pipelines, observability setups, and operational readiness
Exceptional practical problem-solving and analytical skills
Strong written and verbal technical communication skills
Self-learning capability with strong attention to detail