Software Development Engineer III; ML Platform

The Role

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.

As a senior team member, you will guide the design and hands‑on delivery of elegant, strategic code for complex system features. Working closely across teams, you will help navigate technically complex initiatives with high business impact and architectural ambiguity. Success in this role thrives on mutual mentorship to foster team growth, a strong familiarity with key focus areas—such as model serving, training orchestration, or data lineage—and a shared architectural understanding of the MLOps stack.

• Own a core sub‑system, a significant slice of a technology pillar, or complex business‑critical features.
• Lead the design of complex features, services, or new sub‑systems (e.g., component contracts, interface/API designs, SDKs, or high‑throughput data pipelines).
• Directly drive progress on highly complex tasks that involve multiple cross‑functional dependencies, high business impact, or ambiguous requirements. Support vulnerability scanning, management, penetration testing, and incident response.

• Influence team‑level architecture, implementation approaches, and continuous technical improvements.
• Contribute significantly to strategic technical decisions within your specific product, platform, or service area.
• Align technical consensus across team members and represent your team’s sub‑system in cross‑pillar/cross‑team discussions.

• Contribute hands‑on to the most technically challenging parts of the team’s workload.
• Design and implement highly reusable, efficient, and elegant code built for complex requirements and long‑term system strategy.

• Improve team‑level software quality by establishing stronger test coverage, advanced validation patterns, and proactive defect prevention.
• Drive improvements in team CI/CD processes and release quality through automated build, test, and deployment practices.

• Lead the diagnosis and troubleshooting of complex production issues within team systems, improving system resilience and observability.
• Utilize 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.

• Be responsible for creating, reviewing, and maintaining high‑quality technical documentation and durable design knowledge to ensure systems are easily understood and accessible.

• Mentor engineers (SDE I/II) to support their technical growth and review peers’ designs.
• Proactively share skills, knowledge, and technical expertise with members of the engineering team to raise the overall quality bar.
• Actively foster a culture of collaboration, open communication, and continuous learning within the team.

• AI Engineering: our primary consumers — you build the training orchestration, model serving, and registry they use to ship product models, and the dataset and lineage plumbing underneath.
• Research: you give ML researchers fast, reproducible experimentation — experiment tracking, GPU access,…