2 months ago
Lisbon, Portugal or London, United KingdomSenior
Responsibilities
- Build and optimize production ML systems for document classification, extraction, fraud detection, and identity verification.
- Develop repeatable pipelines for training, evaluating, and deploying LLM models.
- Optimize GPU inference for real-time extraction and improve latency, cost, accuracy, and scalability.
- Design advanced labeling workflows and build metrics to measure product and system outcomes.
- Lead technical designs and own complex features from RFC through implementation and production deployment.
- Drive reliability, observability, performance optimization, technical debt reduction, and smooth releases.
- Lead RFCs, critical code reviews, testing, documentation, and technical tradeoff decisions.
- Mentor engineers through pair programming, technical guidance, code reviews, and collaborative problem-solving.
- Coordinate cross-cutting technical solutions across teams and organizational boundaries.
- Partner with Product and cross-functional teams to prioritize features and deliver commitments.
Requirements
- Strong experience building, deploying, and operating complex production systems at scale.
- Hands-on production experience with LLM or ML systems, including model fine-tuning, inference pipelines, latency or cost optimization, or model evaluation.
- Experience with ML frameworks such as TensorFlow, PyTorch, or Triton.
- Deep expertise in at least one area such as ML infrastructure, backend systems, or performance optimization, with broad software engineering knowledge.
- Experience taking complex projects from idea through design, implementation, launch, and production operation with minimal oversight.
- Production service development experience in Python and familiarity with cloud infrastructure.
- Strong understanding of observability, reliability, performance optimization, scalability, and operational practices.
- Demonstrated technical judgment, initiative, pragmatic problem-solving, and ability to make architectural tradeoffs.
- Experience mentoring engineers, providing constructive code reviews, and collaborating across teams.
Benefits
- Career growth support through learning-focused initiatives and challenging work.
- Flexible work options, including hybrid or remote arrangements depending on location.
- London location requires three days onsite; Portugal offers hybrid or remote work.
- Collaborative, inclusive workplace with diversity initiatives, affinity groups, and accessibility support.
Tech Stack
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