Senior ML Engineer (Document Extraction)

Location: Portugal (hybrid or remote) or London, United Kingdom (hybrid, 3 days onsite).

Company

hirify.global develops identity-centric security solutions and identity verification products serving customers across more than 150 countries.

What you will do

• Build document classification and extraction solutions covering thousands of government identity documents globally.
• Design complex features and systems from RFC through implementation and production deployment.
• Develop training, evaluation, and deployment pipelines for LLM-based production systems, optimize GPU inference, and improve labeling workflows.
• Improve production performance, scalability, reliability, observability, and release quality while addressing technical debt.
• Lead RFCs, review critical code, uphold testing and documentation standards, and coordinate cross-team technical solutions.
• Mentor engineers through pair programming, technical guidance, code reviews, and collaborative problem-solving.

Requirements

• Strong experience building, deploying, and operating complex production systems, including observability, reliability, performance optimization, and services at scale.
• Hands-on experience with LLM or ML systems in production, including fine-tuning, inference pipelines, latency or cost optimization, or model evaluation.
• Experience with ML frameworks or systems such as TensorFlow, PyTorch, or Triton.
• Deep expertise in at least one area such as ML infrastructure, backend systems, or performance optimization, together with broad software engineering knowledge.
• Ability to own complex projects end to end, from design and implementation through production, with minimal oversight.
• Production development experience in Python and familiarity with cloud infrastructure; the services also use Ruby and TypeScript and run on AWS with Kubernetes.
• Strong technical judgment, initiative, pragmatic problem-solving, and ability to make trade-offs in ambiguous situations.
• Experience mentoring engineers, guiding junior engineers, conducting constructive code reviews, and collaborating across teams.
• Ability to identify and strategically address technical debt, use empirical evidence, and reason about scalability and reliability constraints.

Culture & Benefits

• Flexible remote, hybrid, and onsite work options depending on location.
• Career growth supported by learning-focused initiatives and challenging work.
• Collaborative environment with cross-functional partnerships, knowledge sharing, and brainstorming.
• Culture emphasizing diversity, inclusion, respect, psychological safety, and continuous improvement.
• Participation in squad-based teams, retrospectives, written RFCs, and DACIs.