25 days ago
Remote, Panama or Panama City, PanamaStaff+
Base Salary
$600k - $1066k/yr
Responsibilities
- Design, build, and operate observability, evaluation, and tooling subsystems for next-generation ML architecture.
- Prove new subsystems through current AIMS operations, including anomaly detection, root cause analysis, and operational automation.
- Build observability systems for model behavior, training pipeline health, serving latency, and data quality.
- Drive cost optimization across AI/ML training and serving infrastructure through increasingly automated frameworks and tooling.
- Architect reliability improvements, reduce operational toil, improve on-call ergonomics, and establish operational excellence standards.
- Contribute to the target architecture and migration path for the modernized AIMS AI/ML stack.
- Evaluate emerging infrastructure patterns, model paradigms, and platform capabilities and translate them into a forward-looking roadmap.
- Coordinate with partner teams, manage dependencies, set technical direction, and build consensus without formal authority.
Requirements
- Significant experience designing, building, and operating production AI/ML systems at scale, including training pipelines and model serving or online inference under high traffic.
- Hands-on experience building orchestration or control subsystems for advanced agentic architectures, such as memory, trace, evaluation, replay, routing, or orchestration layers.
- Strong software engineering fundamentals, deep Python expertise, and working proficiency in Scala or Java.
- Proven experience improving AI/ML reliability, infrastructure cost, and operational scalability.
- Experience building observability and monitoring systems for AI/ML workloads across training, serving, and data pipelines.
- Strong distributed systems background, including large-scale batch processing and real-time serving infrastructure.
- High technical judgment, systems thinking, and the ability to develop reusable frameworks and make pragmatic investment decisions.
- Preferred qualifications include familiarity with LLM evaluation, trace or replay tooling, feature stores, model-serving platforms, experiment frameworks, production AI/ML migrations, and recommendation, search, or discovery systems.
Benefits
- Comprehensive health plans, mental health support, 401(k) retirement plan with employer match, stock option program, disability programs, health savings and flexible spending accounts, family-forming benefits, and life and serious injury benefits.
- Paid leave programs; full-time salaried employees receive flexible time off immediately, while full-time hourly employees accrue 35 days annually for vacation, holidays, and sick paid time off.
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