Senior Applied Scientist (AI)

Location: Fully remote within Colombia; listed locations include Bogotá and Medellín.

Company

hirify.global is a global SaaS company developing AI-powered software for accounting, financial reporting, and audit workflows.

What you will do

• Design and run experiments that measure and improve the quality of LLM-based applications and agents.
• Own evaluation methodology, including benchmarks, regression suites, scoring methods, acceptance thresholds, and offline-to-online performance comparisons.
• Build evaluation infrastructure, synthetic data generation, and eval-builder capabilities for internal teams and customers creating their own agents.
• Develop task-and-verifier structures and contribute statistical methods for agentic memory promotion and demotion.
• Advance self-learning and self-improving systems while validating quality improvements as customers use the platform.
• Influence technical direction through RFCs and design reviews, mentor scientists and engineers, and partner with Platform Engineering, Security, Legal, and domain experts.

Requirements

• 6+ years of professional experience for senior-level candidates, or 8+ years for staff-level candidates, in applied science, machine learning, research, or data-intensive engineering.
• At least 2 years working with production GenAI or LLM-based systems, applications, agents, or related tooling.
• Experience designing and building ML or LLM evaluation frameworks, including metrics, benchmarks, scoring approaches, and rigorous experiment design.
• Strong foundations in probability and statistics, including experimental design, significance testing, and reasoning under uncertainty.
• Ability to build and operate production tooling and services, ideally on AWS, with an understanding of quality, latency, cost, reliability, and safety tradeoffs.
• Strong English communication and collaboration skills; the role is fully remote within Colombia.

Nice to have

• PhD or MS in Computer Science, Statistics, Machine Learning, or a related quantitative field.
• Experience with classical machine learning, model training, MLOps, AI guardrails, governance, or safety mechanisms.
• Experience with distributed, SaaS, cloud-native, or multi-tenant platforms at scale.
• Familiarity with Infrastructure as Code, including CDK, CloudFormation, or Terraform.
• Experience in regulated domains or familiarity with financial audit, accounting, or assurance workflows.

Culture & Benefits

• Permanent full-time employment with legal benefits, prepaid medicine, life insurance, and funeral assistance.
• 100% remote work, home office and internet allowances, and work-life balance support.
• Paid time off, sick leave top-up to 100% of salary from day 3 to day 90, and additional recognition leave.
• Vacation upgrades starting after five years of service and recognition programs.
• Training budget, mentorship, and an AI-first engineering environment focused on independence, innovation, trust, and accountability.
• Work on international SaaS products with a collaborative and globally distributed organization.